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Research Project Booklet 2017/2018 Research Project Booklet

2017/2018

Research

Capabilities

Our innovative research

degree programs provide

advanced academic and

professional research skills

The School of Information Technology & Mathematical

Sciences is the largest information and

communications technology provider in South

Australia, and is regarded as one of the leading applied

mathematics departments in Australia. We offer undergraduate, honours and postgraduate degrees

in information technology, mathematics and statistics,

science, software engineering, data science, and library and

information management. Our programs emphasise the

development of critical thinking, creativity and hands-on

learning to produce graduates who are in high demand.

Research-informed teaching will extend the impact of our

research to almost 40,000 students at UniSA, with

insights from teaching informing and enhancing research.

Research gives teaching distinctiveness and currency by allowing access to the latest thinking, emerging

approaches and new techniques. The involvement of

practitioners in research further enriches teaching and

enhances graduate employability.

The School has 4 research concentrations: • Advanced Computing Research Centre (ACRC) • Phenomics and Bioinformatics Research Centre (PBRC) • Institute for Telecommunications Research (ITR) • Centre for Industrial and Applied Mathematics (CIAM) These 4 areas are committed to solving complex,

real-world problems and in doing so we collaborate

closely with a wide range of national and international

partners from multinational organisations and

government departments through to not for profit

organisations. We work with partners to ensure our research and

consultancy is conducted with an emphasis on applied

knowledge. By working with the School of Information

Technology and Mathematical Sciences, our partners

gain access to world class skills, knowledge, ideas,

facilities and tap into our extensive international network

of leading-edge research.

Research Concentrations

Head of School

Prof Brenton Dansie

Advanced Computing Research Centre (ACRC)

Prof Markus Stumptner

Computational & Theoretical

Neuroscience

Data Analytics Lab

Empathic Computing Lab

Knowledge & Software

Engineering Lab

Strategic Information Lab

Wearable Computer Lab

Centre for Industrial and Applied Mathematics (CIAM)

Prof John Boland

Institute for Telecommunications Research (ITR)

A/Prof Gottfried Lechner

Phenomics and Bioinformatics Research Centre (PBRC)

Prof Stan Miklavcic

Associate Head of Research Education

Prof Jiuyong Li

Future Industries Institute

Affiliated Plans:

Computer and

Information Science

Bioinformatics

Affiliated Plans:

Mathematics

Statistics

Affiliated Plans:

Computer and

Information Science

Affiliated Plans:

Mathematics

Bioinformatics

Affiliated Plans:

Minerals and

Resources

Energy and

Advanced

Manufacturing

Environmental and

Science

Engineering

Biomaterials

Engineering and

Nanomedicine

The Excellence in

Research for Australia

(ERA) 2015, assessed

97% of UniSA’s research

as world standard or

above

Professor Jiuyong Li

Associate Head of Research Education

Research Education Portfolio Leader (REPL)

Cooperative Research Centres (CRC) Winning major participation in 3 CRC’s is

a prestigious achievement for the School

IMCRC integrates technological and

business innovation to significantly

improve Australia’s manufacturing

competitiveness, with a high degree of

interdepend between and across all

programs and projects. IMCRC’s

objective is to help accelerate

diversification of Australian

manufacturing into ‘new

manufacturing’ opportunities and

value chains. As a small high cost

economy, Australia can no longer be

competitive where the basis of

competition is scale and unit cost.

Changes in technology and

international supply chains (exhibiting

increasing complexity and

international disaggregation), together

with new innovative business

organisation, have opened up

opportunities for competitive new

manufacturing. These changes mean

that often, being small is not a

disadvantage, with such

manufacturing typically based on

short runs, high variability, and

rapidity to market, high value and

medium to high complexity.

The IMCRC project, will benefit the

Australian manufacturing industry by

providing them with a new way of

delivering design solutions to end

clients. The project aims to develop a

set of novel Spatial Augmented

Reality (SAR) user interface tools to

allow clients to directly manipulate

designs and will be led by:

Professor Bruce Thomas

Data to Decisions

Cooperative Research

Centre (D2C CRC)

iMOVE Cooperative

Research Centre

The iMOVE CRC will be working on a

new generation of Intelligent

Transport Systems (ITS) technology.

New vehicle-to-vehicle and vehicle-to-

infrastructure connectivity will provide

a platform for the development of a

smarter and more productive

transport system in Australia and

worldwide. These next generation

products, systems and services are

based on higher levels of connectivity,

greater data processing power and

lower operating costs, which will

enhance users’ travel experiences

with richer, real-time data, and more

predictive analysis.

ACRC research within the iMOVE

CRC will focus on data access, data

integration, analytics and fusion,

standards and protocols, legacy

systems and interoperability led by:

Professor Markus Stumptner

The University of South Australia is

the national headquarters for a five

year $88 million Cooperative

Research Centre (CRC) in Big Data

(started in 2014).

The mission of the D2D CRC is to

build capability to unlock the value of

Australia's data. Specifically, the CRC

will focus on arming Industry with the

tools, techniques and workforce to

unlock the value of their data in order

to make business decisions that will

improve their competiveness and

productivity in a global economy.

Led by Dr Sanjay Mazumdar, CEO of

the Defence Systems Innovation

Centre (DSIC), the CRC will initially

focus on research and development

to address the Big Data challenges of

Defence and National Security

(including but not limited to

intelligence, law enforcement, border

security and diplomacy).

Three key projects within the CRC will

be led by ACRC researchers:


(Big Data and Process Management)


(Visualisation)

Professor Jiuyong Li

(Data Mining)

Innovative Manufacturing

Cooperative Research

Centre (IMCRC)

Research

Specialisations

Indicative Projects • Data Mining • Privacy Presentation • Australian Renewable Energy

Agency Project—The Australian

Solar Forecasting System ; • Maintaining cognitive function

in older adults with dementia

using meaningful virtual reality

environments; • Carbon reductions from composting

food waste for food production–

fitting recycling models to urban

forms; • Causal and complex relationship

discovery; • Data mining for Water Management; • Development of high-speed

connections to gather data from earth

observation satellites; • Image processing in Aged Care; • Image processing methods for high

throughput plant phenotyping; • Immersive Information Pod : An

Interactive Visualisation

Environment for Analysts; • Improving accuracy and response

time for satellite based search and

rescue missions; • Interoperability in the oil and gas

industry; • MiRNA & Gene regulation; • Robust and efficient distributed

data storage; • Modelling salt and water transport in

plants; • Social media analysis

for counterterrorism; • Visualisation tools for the design of

manufactured high end instrumented

facilities; • Simulating the brain’s mechanisms

for preventing epileptic seizures; • Designing faster and more efficient

algorithms for automatically

recognising objects in images.

Data Analytics • Data Mining • Privacy Presentation • Learning Analytics • Web Analytics

Human Embedded Systems • Augmented Reality • Wearable Computing • Reconfigurable Computing:

Image processing • Computational Neuroscience • Cognitive Computing

Information Management • Cyber Security and Forensics • Information Quality and Governance • Information Behaviour and Search • Knowledge Management

Telecommunications • Terrestrial and Satellite

Communications • Free Space Optical Communication • Information Theory and

Signal Processing

Mathematics • Mathematical Analysis • Modelling of Systems and

Processes • Optimisation and Optimal Control • Signal and Image Processing • Scheduling & Control for

Transportation • Systems and Water Management • Financial Mathematics and

Risk Management

Phenomics &

Bioinformatics • Plant Phenotyping • Plant Image Processing • Biometrics and Statistics • Computational Biology and

Bioinformatics

Semantic Systems • Data Management, Modelling • Interoperability • Process Analytics • Health Informatics

unisa.edu.au/itms | [email protected] | +61 8 8302 3582

Vacation Scholarships

If you are in your second, third or honours year and have a

strong academic record, a Vacation Research Scholarship will

give you an opportunity to find out whether doing research in

your field of study is your future career direction.

The aims of the vacation research scholarship are to:

Encourage outstanding students who are interested in exploring or wish to pursue a higher degree by research.

Provide the platform to learn about the principles and practices of undertaking research.

Stimulate students’ interest in research and interact with students and staff who are actively involved.

Gauge the research aptitude of the successful applicants

Vacation Research Scholarships give you the opportunity to earn $300 a week undertaking research for up to 8 weeks

with experience researchers, usually between November and February, in a recognised research institute or centre

within the University. The scholarships are offered annually, with applications closing approximately mid-September. To

view the list of available projects and details on how to apply visit: http://www.unisa.edu.au/Research/Research-

degrees/Scholarships/Vacation-Research-Scholarship/#apply

Applying for Postgraduate Studies

We offer a research environment with highly experienced and engaged supervisors, extensive

connections to industry, government and communities, and a focus on addressing globally

significant issues.

The following pages detail the current projects available in the various research concentrations. We encourage you to

connect with our researchers to explore the possibility of enrolling in a PhD under their supervision. It is strongly

recommended that you provide the following documentation in your preliminary enquiry:

1. An up to date CV.

2. Your proposed Research Topic (including a short research proposal statement).

3. Evidence of English Language proficiency.

4. Copies of your Academic Transcripts,

If you are interested in applying for a PhD, visit the University’s research degrees page

(http://www.unisa.edu.au/Research/Research-degrees/) to find out if you are eligible, how to apply and what

scholarships are available.

http://www.unisa.edu.au/Research/Research-degrees/Scholarships/Vacation-Research-Scholarship/#apply

http://www.unisa.edu.au/Research/Research-degrees/Scholarships/Vacation-Research-Scholarship/#apply

http://www.unisa.edu.au/Research/Research-degrees/

http://www.unisa.edu.au/Research/Research-degrees/

Updated 19/06/2017 6 | P a g e

Contents Page

PART 1: Advanced Computing Research Centre 10 Data Analytics Projects

Analytical methods for detection of social media manipulation

Automatic labelling of tweets in civil unrest prediction

Causal data mining methods for discovering adverse drug effects

Causal predication methods for evidence based decision making

Computer vision applications with unmanned vehicles

Develop data mining methods for discrimination detection in data driven decision systems

Developing novel data mining techniques for mining educational data

Discovery and use of Twitter network structural features for civil unrest prediction

Effective time series feature selection for civil unrest prediction using social media data

Efficient Causal Inference in Big Data

Identifying cancer subtypes from multi-levelled biological data with computational methods

Implied Comparative Advantage of Australian Economic Complexity

Integrated Policing: Generating queries for identity resolution

Integrated Policing: Model relationships from text data for identity resolution

Integrated Prediction with Multiple Data Sources and Credibility Assessment

Integration and visualisation of multiple civil unrest prediction models

Interpretable classification and prediction of civil unrest events

Investigating genetic causes of cancer through complex gene regulatory networks

Multimedia Systems (2D and 3D video coding and video streaming, robotics vision, cloud-based video services, panoramic

video analysis, video surveillance and monitoring, multimedia data mining, multimedia sensor networks, medical imaging)

Precursor Pattern Analysis and Interpretable Classification

Prediction of civil unrest events with news and other data sources

Signal processing and analysis for medical imaging

Deep Neural Networks and Parallel Computing Projects

Bio-inspired machine learning and intelligence

Knowledge and Software Engineering Projects

Agile Model-Driven Visualisation of Big Data

Business Process Management for the Internet of Things

Co-Evolution of Linked Lexical Resources

Comparative Evaluation of Natural Language Parsers

Configuration of Software Product Lines

Evolving Knowledge Bases automatically through Natural Language Understanding

Hybrid Approaches to Natural Language Understanding: Integrating (Deep) Machine Learning with Knowledge

Inferring Semantic Relations from Word Co-occurrence Vectors

Knowledge management in genomics

Natural Language Understanding for Automated Understanding of Software Requirements

Ontology-based Information Ecosystems

Patient journey/clinical events analysis

Processes and workflows in clinical genomics

Semantic Interoperability for Big Data

Unstructured Information Management Implementation

Strategic Information Management Projects

Cloud Security

Collaborative Web search (social search)

Connecting to knowledge: Accessing information via the Internet by Indigenous communities

Cybersecurity Policy

Digital Forensics (including Cloud and Mobile Forensics)

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Immigrant youth and children

Information and Communications Technology Leadership

Information Asset Management

Mobile and IoT Security

Online multitasking (Mobile multitasking)

Wearable Computer Projects

A New Projector Based Augmented Reality Precise CAD-Like Manipulations

Augmented Reality Intelligent Tutoring Systems

Augmented Reality Teleconferencing

Deep neural networks for human emotion recognition

Deformable User Interfaces

Disaggregation of Wearable Computation Devices

Empathic Conferencing

Enhancing the social dining experience using augmented reality

Face to Face Collaboration Using HoloLens

Gaze based remote conferencing

Spatial Augmented Reality Design Tools

Storytelling of Big Data

User interaction for interactive constraints and spatial augmented reality

Virtual Reality Brain Training Tools

Visualising and Interacting with Large Graphs of Big Data

PART 2: Centre for Industrial and Applied Mathematics 36

Accurate numerical solutions for satellite orbits

Applied mathematical modelling in nanotechnology

Approximation of Convex Sets

Collision probability modelling for low earth orbit space satellites

Computational Methods for Modelling of Nonlinear Systems

Exact solutions of the Einstein field equations

Forward and inverse electromagnetic scattering

Geometry and geometric issues of atomic nanostructures

Graphene production, and graphene folding and bubbling

Harmonic Analysis: Developing the theory of function spaces on spaces of homogeneous type

High precision modelling of satellite orbits

Modelling methane storage using nano-bottles

Nanoscaled oscillating systems

New methodologies for Nonconvex and Nonsmooth Optimization

Singular perturbations in differential equations

PART 3: Institute for Telecommunications Research 43 Free Space Optical Communications Projects

Adaptive Free-Space Optical Communications

Coding and Signal Processing For Future Fibre-Optical Communications

MIMO and modulations in visible light communications

Positioning by visible light communications

Information Theory Projects

Information theoretic security and privacy

Partial rate region characterisations: new frontiers of information theory

Refinement of fundamental tools in information theory

Networks, Transmission and Coding Topics

Adaptive streaming with delay-constraints

Big Data in Cloud Storage

Distributed control and tracking

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Distributed Transmit Beamforming for Resilient Communications

Fundamental Limits of LPD Communication

Information theoretic security for networks

Network coding for multimedia multicast

Software Defined Radio Projects

Distributed beamforming with SDRs

Waveforms and Algorithms Projects

High speed satellite downlinks

Second Generation Search and Rescue

PART 4: Phenomics and Bioinformatics Research Centre 49

Controlled drug delivery with multi-layered tablets

Creating nanopatterns by dewetting polymer brushes

Deep learning on plant image analysis

Mathematical models for microelectromechanical machines

Modelling of fluid and solute transport in non-uniform, periodic capillaries

Modelling of salt and water transport in plants

Modelling of surface forces in ionic liquids

Sequential data analysis by integrating hidden Markov modelling with domain knowledge

Symmetry methods for nonlinear partial differential equations

PART 5: Future Industries Institute 53

Controlling Nanopatterns from Polymer Brushes

Thin Films from Ionic Liquids

PART 1:

Advanced Computing Research Centre

The Advanced Computing Research Centre

(ACRC) conducts research in a wide variety

of computing areas. These areas include:

Data Analytics, Artificial Intelligence and

Software Engineering, Virtual and Augmented

Reality, and Security and Information

Assurance.

ACRC researchers address complex world

problems by interdisciplinary innovations in

how to understand, model, and visualise the

problems and their solutions. The ACRC has

research links with universities in the USA,

UK, Austria, Canada, China, Germany, Hong

Kong, Japan, Sweden and many more as well

as research connections to companies such

as Intel, Nokia, Canon, Siemens, HP Labs,

Samsung, Jumbovision and Oculus.

Director:


[email protected]

Deputy Director:


[email protected]

Updated 19/06/2017 10 | P a g e

PART 1: Advanced Computing Research Centre (ACRC)

ACRC: DATA ANALYTICS

Analytical methods for detection of social media manipulation

Project Summary: Social media provide tools for people to communicate with each other, on topics of

interest such as travel, shopping, and current affairs. However the anonymity of the Internet means that

social media have been infiltrated by people whose aim is to manipulate the opinions of social media

users, perhaps for commercial or political gain. In this project, we will develop analytical methods and

tools to detect this manipulation. The project aims to identify 'astroturfers' who covertly post under

multiple identities and 'shill' posters who post without disclosing their financial or political interests. The

tools will include forensic linguistics methods and metadata analysis, and will be applied to different

social media types. (Suitable as PhD and Masters project)

Key Words: Computer Science, WebTech and Security

Contact person and details: Associate Professor Helen Ashman

E [email protected]; T 8302 5335; URL http://people.unisa.edu.au/Helen.Ashman

Automatic labelling of tweets in civil unrest prediction

Project Summary: Twitter data is considered as an important open source when predicting civil

unrest events. A number of models have been built with features/patterns extracted from tweets, such

as the volume-based model and planned protest model in (Ramakrishnan et al. 2014), and the

forward-looking approach to crowd behaviour prediction in (Kallus 2014). However, labelling of tweets

still remains a challenging task due to the nature of tweets. In (Zhao et al. 2014), the authors manually

labelled 5386 tweets as civil unrest related, and 6147 as unrelated, which required a large amount of

labor force. The objective of this project is to design and implement either unsupervised or semi-

supervised approaches (Hua et al. 2013), so as to label tweets automatically. (Suitable as PhD and

Masters project)

Key Words: Computer Science, Data Mining

References:

1. Ramakrishnan, N., Butler, P., Muthiah, S., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena,

J., Vullikanti, A., Korkmaz, G., others, 2014. “Beating the news” with EMBERS: forecasting civil

unrest using open source indicators, in: Proceedings of the 20th ACM SIGKDD International

Conference on Knowledge Discovery and Data Mining. ACM, pp. 1799–1808.

2. Kallus, N., 2014, April. Predicting crowd behavior with big public data. InProceedings of the

companion publication of the 23rd international conference on World wide web companion (pp.

625-630). International World Wide Web Conferences Steering Committee.

3. Zhao, L., Chen, F., Dai, J., Hua, T., Lu, C.T. and Ramakrishnan, N., 2014. Unsupervised spatial

event detection in targeted domains with applications to civil unrest modelling. PloS one, 9(10),

p.e110206.

4. Hua, T., Chen, F., Zhao, L., Lu, C.-T. & Ramakrishnan, N. STED: semi-supervised targeted-

interest event detection. KDD’13, 1466-1469.

Contact person and details: Professor Jiuyong Li, Dr Wei Kang

E [email protected]; T 8302 3898; URL http://people.unisa.edu.au/Jiuyong.Li

Causal data mining methods for discovering adverse drug effects

Project Summary: Adverse effects associated with medicines are among the top causes of deaths.

Early detection of adverse effects of medicines will reduce harms to patients and cut the costs for

associated medications. However, given the large amount of drugs and other restrictions, randomised

controlled trials are not always feasible to be conducted to assess drug safety. With the availability of

the large amount of health data in electronic forms and social media discussions about medicines, it is

possible to identify signals of adverse effects and their causes early in such data, as well as to

conduct automated cohort studies using the data to validate the identified signals. This project aims at

developing innovative causal data mining methods to detect the causal signals of adverse effects of

medicines from medical/health data such as medical prescriptions, and open source social media

data. (Suitable as PhD and Masters project)

Key Words: Computer Science, Data Mining, Medical informatics, causal discovery

Reference:

1. M. Pirmohamed, et al. Adverse drug reactions as cause of admission to hospital: prospective

analysis of 18 820 patients," BMJ, vol. 329, no. 7456, pp. 15-19, 2004.

2. R. Harpaz, H. S. Chase, and C. Friedman. Mining multi-item drug adverse effect associations in

spontaneous reporting systems. BMC Bioinformatics, 11(9):1, 2010.

3. Jiuyong Li, Lin Liu, and Thuc Le. Practical Approaches to Causal Relationship Exploration.

Springer, 2015.

mailto:[email protected]

http://people.unisa.edu.au/Helen.Ashman


http://people.unisa.edu.au/Jiuyong.Li

Updated 19/06/2017 11 | P a g e

Contact person and details: Dr Lin Liu, Prof Jiuyong Li

E Lin [email protected]; T 8302 3311; URL http://people.unisa.edu.au/Lin.Liu

Causal predication methods for evidence based decision making

Project Summary: A causal prediction is the forecast of an outcome based on its causes. Evidence

based decision making has a long history of using causal predictions. For example, in medical

domain, researchers often conduct controlled experiments or observational studies to establish causal

relationships and evaluate the effectiveness of treatments as strong evidence for therapeutic

decisions, at population level (e.g. for developing practice guideline) or individual level (e.g. for

personalised medicine). However, such approaches are hypothesis- driven. Firstly a domain expert

presents a hypothesised causal relationship, e.g. between a drug and the recovery of a disease, then

after data has been collected from controlled experiments or observations, the hypothesis is tested on

the data. In many applications, we have an abundance of data available, but we do not know what

causal relationships are hidden in the data. So it is necessary to have data mining tools to

automatically explore the data to find causal evidence. This project aims to develop efficient data-

driven causal prediction techniques to obtain the strongest possible evidence for proper decision

making and interventions. (Suitable as PhD and Masters project)

Key Words: Computer Science, Data Mining, causal discovery, evidence based decision making

Reference:

1. J. Concato, et al. Randomized, controlled, trials, observational studies, and the hierarchy of research design. The New England Journal of Medicine, 342(25):1887–1892, 2000.

2. H.M. Maathuis, et al. Predicting causal effects in large-scale systems from observational data. Nature Methods, 7(4):247-248, 2010.

3. Jiuyong Li, et al. From Observational Studies to Causal Rule Mining. ACM Trans. on Intelligent Syst. and Technology, 7(2):Article 14, 2016


Springer, 2015.

Contact person and details: Prof Jiuyong Li, Dr Lin Liu


Computer vision applications with unmanned vehicles

Project Summary: This project investigates computer vision application on unmanned vehicles, such

as:

1. Robot assisted smart homecare with ambient sensors: Internet of Things in smart home for

detecting potential indoor accidents, 3D model reconstruction of the surrounding for identifying

new objects in 3D space using a robot, human detection and pose analysis to facilitate robot-

based in-situ assistance.

2. Object detection, recognition, and tracking on a UAV: this project applies multi-camera system on

a quadcopter, and algorithms for 3D model reconstruction and new object detection and tracking

will be investigated in this project.

(Suitable as PhD and Masters project)

Key Words: Computer Engineering, Multimedia Systems

References:

1. Kalana Withanage, Ivan Lee and Russell Brinkworth, “Mobile robotic active view planning for

physiotherapy and physical exercise guidance,” IEEE International Conference on Robotics,

Automation and Mechatronics (RAM), Angkor Wat, Cambodia, 2015.

2. Victor Stamatescu, Sebastien Wong, David Kearney, Ivan Lee, and Anthony Milton, “Mutual

information for enhanced feature selection in visual tracking”, SPIE Defense + Security:

Automatic Target Recognition XXV, 2015.

Contact person and details: Dr Ivan Lee

E [email protected]; T 8302 3051; URL http://people.unisa.edu.au/Ivan.Lee

Develop data mining methods for discrimination detection in data driven decision systems

Project Summary: While big data technologies have transformed every aspect of current society, big

data analytics potentially causes social harms in a large scale.

One type of social harms is algorithmic and analytics-enabled discriminations which have been aware

of by top policy makers of USA in a report to former President Obama [1]. The report recommends

that ``The federal government's lead civil rights and consumer protection agencies should expand

their technical expertise to be able to identify practices and outcomes facilitated by big data analytics

that have a discriminatory impact on protected classes, and develop a plan for investigating and

resolving violations of law.''

Unfortunately, very few computational methods [2, 3, 4] for detecting and preventing algorithmic

discriminations in data analytics based decisions are available. This project aims to develop effective

and efficient technologies to support regulatory organisations to detect discrimination cases and for

mailto:Lin%[email protected]

http://people.unisa.edu.au/Lin.Liu




http://people.unisa.edu.au/Ivan.Lee

Updated 19/06/2017 12 | P a g e

various organisations to build discrimination free decision models. (Suitable as PhD and Masters

project)

Key Words: Computer Science, Data Mining, Discrimination, Data driven decision system.

Reference:

1. Whitehouse. Big data: seizing opportunities, preserving values. https://www.whitehouse.gov/sites/default/files/docs/big data privacy report may 1 2014.pdf, 2014.

2. T. Calders and S. Verwer. Three naive bayes approaches for discrimination-free classification. Data Min. Knowl. Discov. 21(2):277–292, 2010.

3. S. Hajian and J. Domingo-Ferrer. A methodology for direct and indirect discrimination prevention in data mining. IEEE Trans. on Knowl. and Data Eng., 25(7):1445–1459, 2013.

4. L. Zhang, Y. Wu, and X. Wu. On discrimination discovery using causal networks. Intl. Conf. on Social Computing, Behavioral-Cultural Modeling, Prediction and Behavior Representation in Modeling and Simulation, 2016.

Contact person and details: Prof Jiuyong Li, Dr Jixue Liu


Developing novel data mining techniques for mining educational data

Project Summary: This project aims to develop data mining techniques for effectively identifying the

factors that influence student academic performance and building better models to predict student

learning outcomes. The increasing adoption of learning management systems, such as Moodle has

enabled education institutions to collect a large amount of data related to student online activities.

Findings from such data can assist the institutions to provide timely and effective student support and

to make interventions. Educational data mining [1] has been attracting more and more research

interests in recent years. However, due to the large volume and high complexity of the data logged by

the learning management systems, traditional data mining methods are facing new challenges to deal

with the big educational data to find out true influential factors on student performance and to build

accurate and interpretable models to predict student outcomes. This project will develop new

methods, such causal discovery approaches [2] to tackle the educational data mining challenges.



References:

1. Cristobal Romero, Sebastian Ventura, and Enrique Garcıa. Data mining in course management

systems: Moodle case study and tutorial. Computers & Education, 51 (1). pp. 368-384, 2008


Springer, 2015.

Contact person and details: Professor Jiuyong Li, Dr Lin Liu


Discovery and use of Twitter network structural features for civil unrest prediction

Project Summary: Social unrest is predicable using Twitter data (Ramakrishnan et al 2014) and the

structures of the Twitter networks are strong indicators. Baltimore riots and Arab Spring share many

similarities in patterns of spread of messages in Twitter (Bohannon 2015). A recent study shows that

there are clear network structure and community changes in Twitter after the 2011 Japanese

earthquake and Tsunami (Lu and Brelsford 2014). Another recent study in PewResearchCenter

characterises six types of conversational structures in Twitters: polarized, tight crowd, Brand clusters,

Community clusters, broadcast network, and support network (Smith et al 2014). This project will

study the methods for extracting structural features in social networks for improving the prediction

accuracy of civil unrest. Some related work for characterisation of Twitter networks can be found in

(Myers 2014, Myers and Shama, 2014). (Suitable as PhD and Masters project)


References:

1. Ramakrishnan, N et al (2014). 'Beating the news' with EMBERS: forecasting civil unrest using

open source indicators. KDD 2014: 1799-1808.

2. Bohannon, J (2015). Can unrest be predicted, Science/AAAS, News May 9.

3. Lu, X and Brelsford, C (2014). Network structure and community evolution on Twitter: human

behavior change in response to the 2011 Japanese earthquake and tsunami, Nature Oct, 2014.

4. Myers, S, Sharma, A, Gupta, P, and Lin, J (2014). The structure of the Twitter follow graph,

Proceedings of International World Wide Web Conference Committee, (IW3C2 14).

5. Myers, S, and Leskovec, J, (2014). The bursty dynamics of the Twitter information network,

Proceedings of International World Wide Web Conference Committee, (IW3C2 14).

Contact person and details: Professor Jiuyong Li








Updated 19/06/2017 13 | P a g e

Effective time series feature selection for civil unrest prediction using social media data

Project Summary: Social unrest events can be modelled by time series and are influenced by other

event series (local, neighbour cities and the major cities), posts in social media, news, and economic

circumstance, etc. The extracted information from the media forms features for building classification

models (Ramakrishnan et al 2014). Each feature is represented as a time series, and the data is a

large set of time series. The aim of the project is to select a subset of time series that are informative

for the prediction the future civil unrest events. Some feature selection work of time series can be

found in (Kim 2012; Sun et al 2012). (Suitable as PhD and Masters project)


References:

1. Ramakrishnan, N et al (2014). 'Beating the news' with EMBERS: forecasting civil unrest using

open source indicators. KDD 2014: 1799-1808.

2. Kim, M (2012). Time-series dimensionality reduction via Granger causality. IEEE Signal

Processing Letters,19(10), 611-614

3. Sun, Y, Li, J, Liu, J, Chow, C, Sun, B, Wang, R (2014). Using causal discovery for feature

selection in multivariate numerical time series, Machine Learning, advance access.

Contact person and details: Professor Jiuyong Li


Efficient Causal Inference in Big Data

Project Summary: Causal inference is a fundamental problem in science. The access to big data has

opened up new opportunities for inferring causal relationships from purely observational data when

experimental tests and interventions are difficult or unethical. Most of existing causal discovery

algorithms are designed for a small and single data set. Thus, big data brings great challenges on

causal inference because of its volume, the diversity of data types and the speed at which it must be

managed. The project will develop efficient and effective causal inference algorithms to deal with big

data challenges for advancing big data mining techniques, and extend those new algorithms to

discover genetic causes of cancer for improving biomedical discovery. The novel causal inference

methods developed in the project will advance data mining techniques and help human beings better

understand cause-and-effect relationships hidden in big data. By extending the research outcomes to

discover genetic causes of cancer to help biomedical researchers understand critical causes and

trends buried in big biomedical data, this will bring great potential to improve biomedical discovery for

better healthcare in Australia. (Suitable as PhD and Masters project)

Key Words: Computer Science

References:

1. Y. Liang and A. R. Mikler. (2014) Big data problems on discovering and analyzing causal

relationships in epidemiological data. IEEE BigData 2014, 11-18.

2. K. Yu, W. Ding, H. Wang, and X. Wu. (2013) Bridging Causal Relevance and Pattern

Discriminability: Mining Emerging Patterns from High-Dimensional Data. IEEE Transactions on

Knowledge and Data Engineering, 25(12): 2721-2739.

3. G. F. Cooper, I. Bahar, M. J. Becich, P. V. Benos and et.al. (2015) The center for causal

discovery of biomedical knowledge from Big Data, Journal of the American Medical Informatics

Association, 1-6.

Contact person and details: Dr Kui Yu, Professor Jiuyong Li


Identifying cancer subtypes from multi-levelled biological data with computational methods

Project Summary: Cancer is a leading cause of death, accounting for more than 8.2 million of

deaths worldwide, or 22,000 people every day. In the past decade, personalised medicine, using

genetic information to develop cancer-specific medication, has become a strong focus for health

researchers. An important step in this personalised medicine framework is to identify cancer subtypes,

as different cancer subtypes may have different treatment therapies. Since cancer is an extremely

complex and heterogeneous disease, the personalised medicine framework relies heavily on

achievements of advanced research in system biology (Wang, 2010). System biology approaches

use knowledge in Mathematics, Statistics and Computer Science to solve the biological problems.

This project will study the computational methods for identifying cancer subtypes using multi types of

biological data. Examples of related works are in (Wang et al. 2014, Liu et al. 2014). Background in

Biology is an advantage but not a compulsory requirement. (Suitable as PhD and Masters project)

Key Words: Computer Science, Bioinformatics

References:

1. Wang E. A roadmap of cancer systems biology. Nature Publishing Group. 2010; 713: 1-28.

2. Wang, Bo, et al. Similarity network fusion for aggregating data types on a genomic scale. Nature

methods. 2014: 333-337.





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3. Liu, Yiyi, et al. "A network-assisted co-clustering algorithm to discover cancer subtypes based on

gene expression." BMC bioinformatics 15.1 (2014): 37.

Contact person and details: Dr Thuc Le, Professor Jiuyong Li

E [email protected]; T 8302 3996; URL http://people.unisa.edu.au/Thuc.Le

Implied Comparative Advantage of Australian Economic Complexity

Project Summary: This project investigates economics complexity at sub-country level in Australia

(with potential extensions to global economies) based on export data within the country or to

overseas, and developing new models for time series predictions of implied comparative advantage.

The outcome of this project will assist policy makers identifying revealed competitive advantages and

opportunity gain for different industrial sections, and predicting the industrial export growth over time.

Students in this project will investigate mathematical modelling and information visualisation of

economic data. This project is supported by the South Australia Department of State Development.


Key Words: Computer Science, Computational Economics

References:

1. The Observatory of Economic Complexity: OEC, https://atlas.media.mit.edu/en/ (last accessed 11

June 2015)

2. Alexander Simoes, Cesar A. Hidalgo, Juan Jimenez, Michele Coscia, Muhammed A. Yıldırım,

Ricardo Hausmann, Sarah Chung, and Sebastián Bustos, “The Atlas of Economic Complexity

Mapping Paths to Prosperity,” https://atlas.media.mit.edu/atlas/ (last accessed 11 June 2015)

3. Ricardo Hausmann, Cesar A. Hidalgo, Daniel P. Stock, and Muhammed A. Yildirim, “Implied

Comparative Advantage,” SSRN Electronic Journal 01/2014; DOI: 10.2139/ssrn.2410427


E Ivan [email protected]; T 8302 3501; URL http://people.unisa.edu.au/Ivan.Lee

Integrated Policing: Generating queries for identity resolution

Project Summary: Identity resolution aims to find whether two records are referring to the same

entity. A lot of work has been done on this topic assuming that the databases containing the two

records to be matched are fully accessible and enabling brute force comparison of all records.

However, this full access assumption becomes impractical in some applications because a database

may be too sensitive to be accessed in any way that a user likes to take. When such a database is

accessed, the user may get only one record per query or get even only true/false answers. In this

case, what queries should be used to access the database so that an identity resolution process can

use the query output to infer identities becomes a serious problem. This project aims to develop

methods and algorithms to generate best queries to access the restricted database for identity

resolution purpose. The query generation would be on the basis of an existing index over similar

entities, e.g., the similar names. (Suitable as PhD and Masters project)


References:

1. Heng Ji. 2015. From Mono-lingual to Cross-lingual: state-of-the-art EDL. Invited Talk at JHU HLT-

COE

2. Heng Ji, Joel Nothman and Ben Hachey. 2014. Overview of TAC-KBP2014 Entity Discovery and

Linking Tasks. Proc. Text Analysis Conference (TAC2014)

3. Dan Roth, Heng Ji, Ming-Wei Chang and Taylor Cassidy. 2014. Wikification and Beyond: The

Challenges of Entity and Concept Grounding. Tutorial at the 52nd Annual Meeting of the

Association for Computational Linguistics (ACL2014)

4. Roy et al (2005). "Towards Automatic Association of Relevant Unstructured Content with

Structured Query Results." CIKM.

5. Gardezi et al (2012). "Query Rewriting using Datalog for Duplicate Resolution." LNCS 7494: 86-

98.

6. Talburt, J., Entity and Identity Resolution. MIT IQ Industry Symposium

http://mitiq.mit.edu/IQIS/2010/Addenda/T2A%20-%20JohnTalburt.pdf, 2010.

7. Christen, P., A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication.

IEEE Transactions on Knowledge and Data Engineering (TKDE), 2012. 24(9): p. 1537-1555.

Contact person and details: Dr Jixue Liu

E Jixue [email protected]; T 8302 3054; URL http://people.unisa.edu.au/Jixue.Liu


http://people.unisa.edu.au/Thuc.Le

https://atlas.media.mit.edu/en/

https://atlas.media.mit.edu/atlas/

mailto:Ivan%[email protected]


http://nlp.cs.rpi.edu/paper/clel.pptx

http://mitiq.mit.edu/IQIS/2010/Addenda/T2A%20-%20JohnTalburt.pdf

mailto:Jixue%[email protected]

http://people.unisa.edu.au/Jixue.Liu

Updated 19/06/2017 15 | P a g e

Integrated Policing: Model relationships from text data for identity resolution

Project Summary: Identity resolution aims to find whether two records are referring to the same

entity. When identity resolution is required from entities in text documents, the task becomes

complicated. One reason is that a documents often refers to many entities and properties of entities

(like names of people) that are not labelled by attributes. At the same time, the relationships among

the entities are described in the documents. For example, a document may contain the sentence

‘Alice saw that Bob drove down Stephen St at 11:00pm’. Here three names are mentioned alongside

of the time entity and the relationships between these names are described. Currently, the methods

dealing with this type of text use Natural Language Parsing tools to extract entities and then put the

entities into relational tables and the match with other relational records of a database. The shortage

of this practice is that the relationships are not used. This project aims to model the entities and the

relationships extracted in text data, and develop ways to compare the modelled entities and

relationships with records in relational databases. The model is expected to be a graph model. The

comparison will need an effective method and an efficient algorithm. (Suitable as PhD and Masters

project)


References:

1. Xiang Ren, Ahmed El-Kishky, Heng Ji and Jiawei Han. Automatic Entity Recognition and Typing

in Massive Text Data. Tutorial at ACM International Conference on Management of Data

(SIGMOD2016)

2. Heng Ji, Joel Nothman and Ben Hachey. 2015. Overview of TAC-KBP2015 Tri-lingual Entity

Discovery and Linking. Proc. Text Analysis Conference (TAC2015)

3. Gardezi et al (2012). "Query Rewriting using Datalog for Duplicate Resolution." LNCS 7494: 86-

98.

4. Bruce, J., et al., Pathways To Identity: Using Visualization To Aid Law Enforcement In

Identification Tasks. Security Informatics, 2014. 3(12).

5. Xu, J., et al., Complex Problem Solving: Identity Matching Based on Social Contextual

Information. Journal of the Association for Information Systems, 2007. 8(10): p. 525-545.

6. Christen, P., A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication.

IEEE Transactions on Knowledge and Data Engineering (TKDE), 2012. 24(9): p. 1537-1555.

Contact person and details: Dr Jixue Liu

E Jixue [email protected]; T 8302 3054; URL http://people.unisa.edu.au/Jixue.Liu

Integrated Prediction with Multiple Data Sources and Credibility Assessment

Project Summary: The research topic will focus on the problems of fusing evidence from multiple

data sources and models, and the credibility of data sources and users. The topic will be based on

the work in Rekatsinas et al. (2015)’s paper on the challenge of discovering valuable sources, Hoegh

et al. (2015)’s paper, in which a Bayesian model fusion framework of protest events is proposed, and

the work in (Mukherjee, Weikum and Danescu-Niculescu-Mizil 2014). (Suitable as PhD and Masters

project)


Reference:

4. Rekatsinas, T et al 2015, Finding Quality in Quantity: The Challenge of Discovering Valuable

Sources for Integration. 7th Biennial Conference on Innovative Data Systems Research

(CIDR‘15) January 4-7, 2015, Asilomar, California, USA

5. Hoegh, A et al 2015, Bayesian Model Fusion for Forecasting Civil Unrest, Technometrics

6. Mukherjee, S., Weikum,G, and Danescu-NiculescuMizil C 2014, People on drugs: credibility of

user statements in health communities. In KDD’14, pages 65-74

Contact person and details: Dr Lin Liu


Integration and visualisation of multiple civil unrest prediction models

Project Summary: A complete system often consists of multiple models/components, which work and

interact with each other to provide expected results. The objective of this project is to integrate

multiple existing civil unrest prediction models (Ramakrishnan et al 2014) into one system, and make

sure all the components work properly together to provide a comprehensive and user-friendly result

through user interface and visualisation. (Suitable as PhD and Masters project)


References:

1. Ramakrishnan, N., Butler, P., Muthiah, S., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena,

J., Vullikanti, A., Korkmaz, G., others, 2014. “Beating the news” with EMBERS: forecasting civil

unrest using open source indicators, in: Proceedings of the 20th ACM SIGKDD International

Conference on Knowledge Discovery and Data Mining. ACM, pp. 1799–1808.

Contact person and details: Professor Jiuyong Li, Dr Wei Kang

mailto:Jixue%[email protected]

http://people.unisa.edu.au/Jixue.Liu



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Interpretable classification and prediction of civil unrest events

Project Summary: The lack of interpretability makes many sophisticated classification/regression

models infeasible in real applications, which place great emphasis on both the accuracy and

comprehensibility of the potential models, such as medical scoring systems (Letham et al. 2015). The

goal of the project is to build interpretable prediction models with patterns, which are easy for human

reasoning and understanding. There is recent progress on Bayesian analysis (Letham et al. 2015)

and discriminative pattern-based classification (Shang et al. 2016; Lou et al. 2013). The patterns or

high-order features that are highly correlated to the target civil unrest events will be used as the input

of the building of the models. The student may compare the performance of the two major

interpretable models in the context of predicting civil unrest events, and explore a new way of

interpretable prediction model, e.g. through the combination of the two approaches. (Suitable as PhD

and Masters project)


References:

1. Letham, B. et al (2015). "Interpretable classifiers using rules and Bayesian analysis: Building a

better stroke prediction model." The Annals of Applied Statistics 9.3 (2015): 1350-1371.

2. Shang, J., et al. (2016). An Effective but Concise Discriminative Patterns-Based Classification

Framework. In Proceedings of 2016 SIAM International Conference on Data Mining (SDM 2016)

3. Lou, Y. et al (2013). Accurate intelligible models with pairwise interactions. In SIGKDD, 2013,

623–631

Contact person and details: Professor Jiuyong Li, Dr Jie Chen


Investigating genetic causes of cancer through complex gene regulatory networks

Project Summary: This project will study the computational methods for identifying the genetic

causes of cancer through gene regulatory networks containing multiple gene regulators. Gene

regulatory networks play an important role in every process of life, and understanding the dynamics of

these networks helps reveal the mechanisms of diseases. There have been tremendous works on

inferring gene regulatory networks. However, most of the works consider the networks with only one

type of gene regulator, such as transcription factors (Imam et al., 2015) or microRNAs (Le, 2013), thus

only help reveal part of the whole regulatory network picture. This project aims to develop methods to

construct gene regulatory networks that contain multiple types of gene regulators and methods to

isolate sub-networks that are altered between normal and cancer patients. Examples of related works

are in (Le et al. 2013, Ping et al. 2015). Background in Biology is an advantage but not a compulsory

requirement. (Suitable as PhD and Masters project)

Key Words: Computer Science, Bioinformatics

References:

1. Imam, Saheed, Daniel R. Noguera, and Timothy J. Donohue. "An Integrated Approach to

Reconstructing Genome-Scale Transcriptional Regulatory Networks." PLoS computational

biology 11.2 (2015): e1004103-e1004103.

2. Le, Thuc D., et al. "Inferring microRNA–mRNA causal regulatory relationships from expression

data." Bioinformatics 29.6 (2013): 765-771.

3. Le, Thuc D., et al. "Inferring microRNA and transcription factor regulatory networks in

heterogeneous data." BMC bioinformatics 14.1 (2013): 92.

4. Ping, Yanyan, et al. Identifying core gene modules in glioblastoma based on multilayer factor-

mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data.

Nucleic acids research 43.4 (2015): 1997-2007.

Contact person and details: Dr Thuc Le, Professor Jiuyong Li

E [email protected]; T 8302 3996; URL http://people.unisa.edu.au/Thuc.Le

Multimedia Systems (2D and 3D video coding and video streaming, robotics vision, cloud-based video services, panoramic video

Project Summary: Multimedia systems use a combination of content forms to facilitate media rich

applications such as video conferencing or robotics vision. The multimedia projects we offer include

either software or hardware design, developing applications for mobile devices (smart phone, tablets),

desktop computers, robots, embedded systems, or high-performance computers (such as clusters or

cloud computers.) The candidates will have opportunities to utilise different sensors, such as 2D and

3D video cameras, microphone arrays, marker/visual-based tracking systems, or the Australian

Synchrotron, for different projects.

Potential projects include, but not limited to:

2D and 3D video coding



http://www.thefreedictionary.com/comprehensibility




http://people.unisa.edu.au/Thuc.Le

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analysis, video surveillance and monitoring, multimedia data mining, multimedia sensor networks, medical imaging)

Compressive video coding

Free-viewpoint video coding and streaming

Cloud-based video streaming

Vision system for unmanned aerial vehicle (UAV), Unmanned ground vehicle (UGV), or

autonomous underwater vehicle (AUV)

Wireless multimedia sensor networks

Medical imaging

Biomechanics using computer vision


Key Words: Computer Engineering



Precursor Pattern Analysis and Interpretable Classification

Project Summary: The aim is to develop new pattern discovery methods on large-scale unstructured

online data to derive useful relationships among instances of variables, especially targeted at those

messages prior to the civil unrest events so that interpretable prediction models with causal

relationships can be learned based on the methods developed in (Letham et al. 2013; Li, Liu and Le

2015). (Suitable as PhD and Masters project)


References:

1. Letham, B et al 2013, Interpretable classifiers using rules and Bayesian analysis: Building a better

stroke prediction model. Technical Report no. 609, University of Washington, August 2013.

2. Li, J., Liu, L., and Le, T. 2015, Practical approaches to causal relationship exploration, Springer,

2015

Contact person and details: Dr Lin Liu


Prediction of civil unrest events with news and other data sources

Project Summary: Tweets have played an important role in the prediction of civil unrest events, such

as protests, and may provide insights into the root causes of the events. However, online news feeds,

blogs and other sources e.g. economic time series and GDELT data, are also useful in the forecasting

of these events (Ramakrishnan et al. 2014). The informative patterns discovered from the news

sources, e.g. interactive patterns (Ning et al.2015) and precursor patterns (Ning eg al. 2016), can be

utilised in enhancement of existing predictive models that majorly rely on twitter data. (Suitable as

PhD and Masters project)


References:

1. Ramakrishnan N., Butler P., Muthiah S, et al. “Beating the news” with EMBERS: forecasting civil

unrest using open source indicators. KDD ′14, New York, ACM, August24–27, 2014 pp. 1799–

1808

2. Yue Ning, Sathappan Muthiah, Ravi Tandon, Naren Ramakrishnan: Uncovering News-Twitter

Reciprocity via Interaction Patterns. ASONAM 2015: 1-8

3. Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan: Modelling Precursors for

Event Forecasting via Nested Multi-Instance Learning. CoRR abs/1602.08033 (2016)

Contact person and details: Professor Jiuyong Li, Dr Jie Chen


Signal processing and analysis for medical imaging

Project Summary: This project will investigate sparse signal reconstruction for computed

tomography and particle image velocimetry analysis, on synchrotron phase contract x-ray images, to

overcome challenges on detecting and tracking overlapping particles for the assessment of cystic

fibrosis airway therapies. This project can also apply similar algorithm for different medical imaging

techniques, such as MRI, ultrasound, and confocal microscopic images. (Suitable as PhD and

Masters project)

Key Words: Computer Engineering, Multimedia Systems

References:

1. Zhenglin Wang and Ivan Lee, "Backprojection Regularization with Weighted Ramp Filter for

Tomographic Reconstruction", International Conference of the IEEE Engineering in Medicine and

Biology Society (EMBC), Milan, Italy, 2015.

2. Hyewon Jung, Ivan Lee, Sang-Heon Lee, “Circular Particle Detection using Sectored Ring Mask

for Synchrotron PCXI images,” International Conference of the IEEE Engineering in Medicine and

Biology Society (EMBC), Milan, Italy, 2015.




http://www.springer.com/computer/ai/book/978-3-319-14432-0





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ACRC: DEEP NEURAL NETWORKS AND PARALLEL COMPUTING PROJECTS

Bio-inspired machine learning and intelligence

Project Summary: Engineered technology and biological brains share many common features. For

example, brains have evolved ways to (i) acquire information (sensing), (ii) communicate between

brain regions (information transmission) and (iii) form and recall memories (information storage).

Improved knowledge about these processes is essential for understanding how our brains "compute."

The goal of this project is to use insights from computational neuroscience to design bio-inspired

machine learning algorithms and devices. This project will potentially contribute to future technologies,

as well as "neural engineering" techniques for enabling direct communication between neurons in the

brain and external electronics, such as "bionic eyes" and brain-machine interfaces. (Suitable as PhD

project)

Key Words: Computational and theoretical neuroscience

Contact person and details: Associate Professor Mark McDonnell

E [email protected]; T 8302 3341; URL http://people.unisa.edu.au/Mark.McDonnell

ACRC: KNOWLEDGE AND SOFTWARE ENGINEERING Agile Model-Driven Visualisation of Big Data

Project Summary: Data visualisation and visual analytics are more frequently used in recent years to

describe and explore data in an easy to understand way. One of biggest challenges is to provide

flexible visualisation techniques and guidelines on when to apply a particular visualisation technique.

This project will investigate a new paradigm, agile visualisation (http://agilevisualization.com/) in

combination with Model Driven Engineering (MDE) to provide increased flexibility to develop

personalised visualisation and develop design guidelines to help the end user to identify the optimal

visualisation by supporting the whole life cycle of visual analytics.

Data will be provided by local industry partner Active Operations Management (AOM) which makes

this project a very interesting applied research project with high relevance to the local industry.

(Suitable as PhD project)

Key Words: Visual analytics, software engineering, model driven engineering, agile visualisation

Contact person and details: Dr Georg Grossmann

E [email protected]; T 8302 3194; URL http://people.unisa.edu.au/Georg.Grossmann

Business Process Management for the Internet of Things

Project Summary: Within the last few years, business process management has evolved from the

abstract handling of software applications involving users in front of screens that are separated from

real world events to the provision of dynamic, interoperating services that are directly linked to each

other in vast, planet-spanning process networks. In addition, emerging network-enabled smart device

standards have led to the so-called “Internet of Things” (IoT) which allows software systems to

remotely access and control devices. This has become a priority research topic in the EU, US, and

Asia and is heralded as “the next technology revolution” in a February 2013 special issue of IEEE

Computer, leading to the incorporation of IoT technology into Web applications has led to the Web of

Things (WoT). This has triggered the call for business process modelling techniques to catch up.

Assumptions that have shaped much for business process management for decades, no longer hold

in the new, distributed, real world connected environment: the assumption of a perfect world (i.e.,

events happen as they are planned), e.g., an airplane arrives exactly at the time for which its

scheduled), and the assumption of a perfect system (events become immediately known when they

occur). A fundamental property of the new generation of business processes is therefore that they

need to be time aware. An event has to be analysed not just in terms of what immediate action it

requires in response, but how the event and that action are going to affect and possibly interfere with

steps and expected events already planned for in the future. Potential key topics to be explored

include:

A declarative method to specify bitemporal business rules instead of traditional automata net

representations

A business rule language for formal characterisation of the different time-aware event processing

situations

Descriptions of how to react to events or constraint violations (e.g., pro-, or retro-actively), and for

linking these to business processes. occurrence time)




http://people.unisa.edu.au/Mark.McDonnell


http://people.unisa.edu.au/Georg.Grossmann

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Case studies to demonstrate these techniques in realistic, large-scale environments


Key Words: Software Engineering, Artificial Intelligence

References:

1. Opher Etzion. Event processing - past, present and future. PVLDB, 3(2):1651–1652, 2010.

2. Tim Furche, Giovanni Grasso, Michael Huemer, Christian Schallhart, and Michael Schrefl.

Bitemporal complex event processing of web event advertisements. In Proc. WISE (2), pages

333–346, 2013.

3. Alejandro P. Buchmann, Stefan Appel, Tobias Freudenreich, Sebastian Frischbier, and Pablo

Ezequiel Guerrero. From Calls to Events: Architecting Future BPM Systems. In Proc. Intl. Conf.

on Business Process Management (BPM), LNCS 7481, pages 17–32. Springer-Verlag, 2012.

4. Internet of Things: Strategic Research Roadmap. Technical report, Cluster of European Research

Projects on the Internet of Things (CERP-IoT), 2009.

Contact person and details: Professor Markus Stumptner

E [email protected]; T 8302 3965; URL http://people.unisa.edu.au/Markus.Stumptner

Co-Evolution of Linked Lexical Resources

Project Summary: In this era of Big Data, Natural Language Understanding (NLU) applications must

link to, query, and integrate knowledge from a variety of internal and external sources (e.g.,

knowledge graphs, ontologies, and domain models) to arrive at the understanding of a piece of text. In

our work with the Defence Science and Technology Group, for example, reading text that describes

the behaviour of entities in combat simulations requires the integration of models of actions that can

be performed (e.g., move and attack), while the entity types themselves (e.g., soldiers and tanks) are

defined in a separate ontology and individual entities may be stored in yet another knowledgebase.

The NLU application must be able to connect elements of the text to the entity types, entities, and

behaviours maintained in the different knowledge-sources; this is done through a common lexical

layer linking words (morphology), syntax, and semantics. This layer provides a common ground for

integrating knowledge from different sources through language use and is a key component of

advanced Natural Language Understanding techniques. However, the lexical layer requires extensive

management to ensure consistency between the three aspects. For example, the lexicon itself may be

updated to incorporate new terminology, synonyms, etc., or the knowledgebase constituting the

semantics of the lexical entries may be revised such that the lexical entries need to reflect the change.

Modifying the syntactic rules or semantic elements of a knowledgebase may lead to the lexicon being

out-of-date, resulting in incorrect analyses of text.

This project will investigate means of (semi-)automatically updating a shared lexicon as the result of

changes to different knowledge-sources in an NLU application. A common framework for ontology and

model adaptation should be developed along with techniques of analysing these adaptation models to

propagate changes in knowledge-sources to the lexical entries referencing them. The final result will

include a prototype implementation integrated with the NLU framework being developed within the

Knowledge and Software Engineering Laboratory. (Suitable as PhD Project)


Contact person and details: Professor Markus Stumptner, Dr Wolfgang Mayer, Dr Matt Selway


Comparative Evaluation of Natural Language Parsers

Project Summary: Recently, Google opened-sourced their Natural Language Parser and many

groups promoted or released their own in response, providing a slew of state-of-the-art parsers for

academics and organisations to use in their work. At the same time, there are many commonly used

parsers, such as the Stanford Parser, that are widely considered to provide good results. However,

there is no high-quality, academically rigorous, and comparable evaluation of these parsers: old or

new. This project will produce a comparative evaluation of the currently available Natural Language

Parsers, including both older parsers and those newly released. The project includes the design and

execution of a systematic evaluation performed on common test corpora and will form the basis for the

comparison of the Natural Language Understanding engine being developed within the Knowledge

and Software Engineering Laboratory. (Suitable for PhD, Masters, and Vacation Scholarship)

Key Words: Natural Language Processing, Software Engineering, Evaluation

Contact person and details: Professor Markus Stumptner, Dr Matt Selway



http://people.unisa.edu.au/Markus.Stumptner





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Configuration of Software Product Lines

Project Summary: In many markets today, customers no longer consider customization as special:

they expect it. This expectation applies both to simple goods like t-shirts and to more sophisticated

products composed of heterogeneous hardware, software and services. Yet, the complexity in

engineering and manufacturing of deeply configurable products varies significantly. Numerous

sectors, such as automotive, semiconductors, and cloud services, lack tools and methods to keep

their hardware and software configurations consistent during configuration and evolution. Ad hoc

solutions frequently patch isolated problems, but fail to effectively improve overall key performance

indicators such as availability, reliability and time-to-market. Integrated solutions to align software,

hardware and service configuration are missing. Research in configuration is currently carried out in

two main communities: (hardware) product configuration and software configuration. Despite the

significant overlap in research interests, they have evolved mainly in isolation. Yet, similar challenges

and solutions have emerged in both communities.

The goal of this project is to examine the modelling methods used for product configuration (a well-

established industrial application area) and examine what benefits they can provide for Software

Product Line Engineering. (Suitable as PhD project)


Contact person and details: Professor Markus Stumptner, Dr Wolfgang Mayer


Evolving Knowledge Bases automatically through Natural Language Understanding

Project Summary: Over the last ten years, a number of projects such as DIRT, NELL (the

NeverEnding Language Learner), BKB and others [1,2,3,4] have been started with the goal of learning

the content of large knowledge bases from text documents. However, most of these systems study

only the learning process in general. To make such systems relevant in practice, they must produce

useful knowledge for particular applications and must be able to consider the relevance of prior

knowledge when reading new text. This project will study the question of how additional knowledge

can be learned from text and merged with an existing knowledge base, resulting in a process that can

gain and retain competence in a real world context throughout years of use. (Suitable as PhD Project)

This work is aligned with the ‘Doctrine to Code’ project funded by the Australian Defence Science and

Technology Organisation (DSTO). (Suitable as PhD project)


References:

1. L. Schubert, Can we derive general world knowledge from text? in Proc. HLT, 2002, pp. 94–97.

2. P. Clark and P. Harrison, Large-scale extraction and use of knowledge from text, in Proc. 5th

KCAP, 2009, pp. 153–160.

3. D. Lin and P. Pantel, DIRT: Discovery of inference rules from text, in Proceedings of the ACM

SIGKDD Conference on Knowledge Discovery and Data Mining, 2001, pp. 323–328.

4. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. Hruschka, Jr., and T. M. Mitchell, Toward an

architecture for never-ending language learning, in Proc. AAAI, 2010, pp. 1306–1313

5. Matt Selway, Georg Grossmann, Wolfgang Mayer, Markus Stumptner: Formalising Natural

Language Specifications Using a Cognitive Linguistics/Configuration Based Approach.

Proceedings Enterprise Computing Conference 2013.



Hybrid Approaches to Natural Language Understanding: Integrating (Deep) Machine Learning with Knowledge

Project Summary: Natural Language Understanding (NLU), the ability for computers to comprehend

language to the same degree as a person so that they can perform actions and respond to complex

queries, is an ongoing challenge. For the last two decades, the focus of Natural Language Processing

has been on using Machine Learning techniques to train models for specific tasks, for example, Part-

of-Speech tagging, Syntactic Parsing, Sentiment Analysis, and Named-Entity Recognition. Moreover,

the recent trend of Deep Learning (i.e., the training of layered neural networks) is being applied to

NLP tasks to improve performance over traditional Machine Learning techniques.

While such approaches have been quite successful in obtaining usable results in many applications,

they have their limitations and, hence, cannot realise Natural Language Understanding on their own.

Chief among the limitations of Machine Learning methods is their inability to make use of existing

knowledge resources such as lexical resources (WordNet, VerbNet), ontologies, knowledge-graphs,

domain models, etc. These knowledge resources provide the link between human and computer

understanding; therefore, being able to incorporate them is a necessity to achieve NLU.

In contrast, non-Machine Learning approaches to NLP (i.e., symbolic, rule, or knowledge-based

approaches) can readily incorporate various knowledge resources. This allows them to perform NLU

within a restricted application domain or context; however, they lack the ability to generalise across

the large amount of data available in today's world. Instead new rules must be added manually, new



http://www.dblp.org/pers/hc/s/Selway:Matt.html

http://www.dblp.org/pers/hc/g/Grossmann:Georg.html

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knowledge-sources must be manually integrated, and large data sources may lead to inefficiencies in

processing text, if they can be incorporated at all. Therefore, to realise general NLU capability, the two

approaches must be combined.

This project aims to develop a hybrid approach to Natural Language Understanding that integrates

Machine Learning and Deep Learning with Knowledge-based approaches. It will investigate which

aspects of Natural Language Understanding can make best use of Machine Learning and Knowledge-

based components and integrate them in a prototype NLU system being developed in the Knowledge

and Software Engineering Laboratory. (Suitable as PhD Project)




Inferring Semantic Relations from Word Co-occurrence Vectors

Project Summary: A common technique in Natural Language Processing, popularised by Google’s

word2vec, is to analyse a corpus of text to produce co-occurrence vectors for each word (basically the

vectors contain one dimension per word pair), which enables us to determine the similarity between

two words. Such vector models, or distributional semantics, demonstrates some neat properties: for

example, subtracting the vector for 'man' from the vector for 'king' and adding the vector for 'woman'

results in a vector very close to that of 'queen'. However, such models are limited, finding most use in

indexing and information retrieval (such as Google's search engine), tend to focus on nouns, and are

not truly semantic. For example, two word vectors may be close together, not because they are similar

concepts, but because they are strongly related through some (unknown) relationship. These

relationships are often identifiable by the verbs and prepositions used between them. This project

aims to be a starting point for inferring semantic relations between word co-occurrence vectors by

incorporating the co-occurrence information of prepositions and verbs. The candidate will develop an

initial prototype that will identify basic semantic relations (such as parthood, and more general/more

specific terms) from key prepositions as well as a small set of domain specific relations of interest.

(Suitable for PhD, Masters, and Vacation Scholarship)

Key Words: Knowledge Acquisition, Machine Learning



Knowledge management in genomics

Project Summary: Genomics (and indeed other “omix”es) are generating big amounts of data.

These can be classified into essentially 3 categories:

1. Research data

2. Clinical data

3. Reference data

At this stage, lots of effort is to build large and high quality databases capturing reference data on

gene variants, as this is a condition sine qua non for clinical evaluation of medical genetic testing

results.

There are several significant problems with such databases:

1. Assessment of pathogenicity and maintaining this assessment current (i.e. there should be a

regular review of pathogenicity assessment at least for variants deemed pathogenic) – this is the

problem with curation (as described later), but serious preparation can be done automatically

(e.g. by regularly scanning other databases, literature and in future possibly Electronic Health

Records) to detect any patterns indicating the specific variant requires (human) review.

2. Assembling and management other knowledge (from external sources?) on each variant - at

least the pathogenic ones (integration of pieces of knowledge opens questions on how to

capture/represent/resolve possible contradictions in evidence/opinion)

3. Phenotype link to the variant (I assume electronic health records should be a possible source for

this information – PCEHR nation-wide – and EPAS in South Australia might be a good place to

start experimenting).

4. Curation of the database – the load on curators is growing rapidly, so it cannot be a voluntary

commitment any more (as it used to be in the past). However, the practice is lagging behind and

such position (paid enough to attract senior experienced person) is not easy to establish. Hence

the idea offers itself to look at “crowdsourcing” – i.e. whether the curation task can be (with

serious support of IT) distributed amongst members of the community.

To support such work we have a good working relationship with SA Pathology (experts in genetics

and genetic testing) and Human Variome Project (world-wide initiative collecting data on human

variome). (Suitable as PhD project)

Key Words: Computer Science, Health/clinical informatics

Contact person and details: Dr Jan Stanek



https://code.google.com/archive/p/word2vec/



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E [email protected]; T 8302 3460; URL http://people.unisa.edu.au/Jan.Stanek

Natural Language Understanding for Automated Understanding of Software Requirements

Project Summary: Automated construction of software is a long-held dream of Computer Scientists

and Software Engineers. With the advent of ‘Model driven engineering’, it has moved closer to reality

as systems need no longer be developed in low level code but can be specified in terms of diagrams

of behaviour specified in languages such as UML. This project will build on earlier work to create a

system that can understand natural language text describing a particular application domain and

converts it into diagrams that can be executed. (Suitable as PhD project)

This work is aligned with the ‘Doctrine to Code’ project funded by the Australian Defence Science and

Technology Organisation (DSTO).


References:

Matt Selway, Georg Grossmann, Wolfgang Mayer, Markus Stumptner: Formalising Natural Language

Specifications Using a Cognitive Linguistics/Configuration Based Approach. Proceedings Enterprise

Computing Conference 2013.



Ontology-based Information Ecosystems

Project Summary: Flexible data integration has been an important IT research goal for decades.

About ten years ago, a significant step was taken with the introduction of declarative methods (e.g.,

Clio). Since this work, mostly based on classic dependency analysis, extensions have been developed

that express more powerful semantic relationships. However, much of this work has remained focused

at the relational database (i.e., relatively low) level, and many of the extensions revert to specific

algorithms and function specifications. At the same time, models have evolved to incorporate more

powerful semantics (object or ontology-based methods). Work in this area will focus on combining

separate but currently unrelated efforts for a coordinated approach to engineering interoperability.

Use of major existing upper ontologies (e.g., DOLCE)

Incorporation of new modelling concepts such as role relationships

Incorporation of engineering ontologies (e.g., the NASA measurement ontology)

Testing using current activities related to multiple engineering standards ranging from air traffic

management over health to the oil and gas industry.

This work is aligned with the International Oil & Gas Interoperability Pilot (partners Assetricity, IBM,

Microsoft, Bentley, AVEVA, Intergraph, Rockwell Automation), and the Oil & Gas Interoperability

Project funded by the SA State Government. (Suitable as PhD project)

Key Words: Software Engineering, Data Management, Ontologies, Artificial Intelligence

References:

1. Mayer, W., Stumptner, M., Grossmann, G., Jordan, A. (2013). Semantic Interoperability in the Oil

and Gas Industry: A Challenging Testbed for Semantic Technologies, AAAI Fall Symposium 2013

on Semantics for Big Data.

2. Schneider, T., Hashemi, A., Bennett, M., Brady, M., Casanave, C., Graves, H., Gruninger, M.,

Guarino, N., Levenchuk, A., Lucier, E., Obrst, L., Ray, S., Sriram, R. D., Vizedom, A., West, M.,

Whetzel, T., Yim, P. (2012). Ontology for Big Systems: The Ontology Summit 2012 Communique,

Applied Ontology 7(3), pages 357-371.

3. Teymourian, K., Coskun, G, and Paschke, A. (2010). Modular Upper-Level Ontologies for

Semantic Complex Event Processing. In Proc. of the 2010 conference on Modular Ontologies:

(WoMO 2010), IOS Press, pages 81-93

Contact person and details: Prof Markus Stumptner, Dr Wolfgang Mayer, Dr Georg Grossmann


Patient journey/clinical events analysis

Project Summary: Analysis of event sequences along the path of diagnosing and treating a patient

can establish an important basis for performance (in terms of quality of care, safety of care and cost of

care) management in health care. The research required in this area spans from data mining (path-

mining, workflow mining), through to models of the patient journey and assessing the clinical/fiscal

outcomes across such models. Major challenges in this area are:

Clinical data extraction and preparation for analysis (issues such as confidentiality of the data;

reconciliation of data formats, data schemas and diverse ontologies - I expect use of UMLS

metathesaurus and other ontologies to be utilized to reconcile data from different sources; data

linkage)

Finding effective approaches to handle very rich and diverse information (data in health is seldom

complete or consistent) – methods developed for data analytics in business may not be valid in

this situation and re-validation of such algorithms may be required


http://people.unisa.edu.au/Jan.Stanek

http://www.dblp.org/pers/hc/s/Selway:Matt.html

http://www.dblp.org/pers/hc/g/Grossmann:Georg.html

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Researching (exploration, modelling) of processes involved in such analysis in order to support

automation of the event analytics in clinical practice

Partners from SA Health will be sought - subject to specific project approval and ethics clearance.





Processes and workflows in clinical genomics

Project Summary: Genetic testing is a highly dynamic area of research spanning several groups of

specialists: clinicians, clinical geneticists, medical scientists, laboratories, and bioinformaticians (to

name the main ones). Members of these groups use different terminologies, may have different

objectives and come from different professional cultures.

Clinicians come from medical background (with limited depth of molecular biology knowledge) and

their main objective is to use genetic testing for better diagnosis and treatment of a given cohort of

(cancer) patients. Main issues for this group are: when the genetic testing is indicated, and how to

interpret the results. This is in stark contrast with e.g. bioinformaticians, who come from mathematical

and biology background (with very little clinical basis and exposure). Their objective is to process

massive data produced by genetic testing (such as exom sequencing) to generate a validated result.

Incorporation of genetic testing into clinical practice represents a challenge:

How we can design a set of processes which would allow integration of activities of such a

diverse group of specialists?

How we have to reconcile the differences in terminology each group of specialists is using?

What information is needed to support processes (and decision-making) at a given group of

specialists?

And how we have to design the process so that they are robust enough to cope with frequent

changes and editing (NB: all layers of genetic testing are rapidly evolving) without creation of

internal inconsistencies and contradictions?

The proposed research is to explore the application of process mining (to learn what processes are

currently used) and dynamic process modelling and integration (at semantic level – this includes

integration of ontologies as well) to design a federated, hierarchical model describing activities from

test ordering through genetic counselling, laboratory analysis, result generation, validation and

interpretation, back to clinical interpretation and use. The research will build on knowledge and tools

developed in the Semantic Systems Group. (Suitable as PhD project)


Partners: Centre for cancer biology; SA Pathology – Flinders Medical Centre.

Colleagues for the partner organisations will participate in student supervision.



Semantic Interoperability for Big Data

Project Summary: Big Data is the “new oil” – the substance that is expected to drive the information

economy of tomorrow. Big Data applications and projects are everywhere and companies prepare for

the future where they cannot survive without the information gleaned from a variety of data sources. It

is this variety (the third of the three ‘V’s associated with Big Data: volume, velocity, and variety) that

Variety refers to the need to deal with many different data sources and data formats. This project will

examine the use of semantics (i.e., background knowledge about the data) for the effective

combination of different data sources that is a prerequisite for data mining. (Suitable as PhD project)

The work is aligned with the $88 Million Data to Decision Collaborative Research Centre (D2D CRC).

Key Words: Computer Science, Data Management, Ontologies

References:

1. Berger, S., Grossmann, S., Schrefl, M., and Stumptner, M. (2010). Metamodel-Based Information

Integration at Industrial Scale. In Proc. of the 13th ACM/IEEE Conference on Model Driven

Engineering Languages and Systems (MODELS), pages 153-167, Springer.

2. Feiler, E. et al. (2006). Ultra-Large-Scale Systems: The Software Challenge of the Future.

Software Engineering Institute, CarnegieMellon.

3. Stonebraker, M., Bruckner, D., lyas, I., Beskales, G., Cherniack, M., Zdonik, S., Pagan, M., Xu, S

(2013). Data Curation at Scale: The Data Tamer System. 6th Biennial Conference on Innovative

Data Systems Research (CIDR’13), Asilomar, California.

4. Stonebraker, M., Madden S., Debey P. (2013) Intel “Big Data” Science and Technology Center

Vision and Execution Plan. SIGMOD Record 42(1).

5. Knoblock, C., Szekely, P. (2015) Exploiting Semantics for Big Data Integration. AAAI Magazine,

Spring 2015.





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Contact person and details: Prof Markus Stumptner, Dr Wolfgang Mayer, Dr Georg Grossmann


Unstructured Information Management Implementation

Project Summary: Modern text analysis applications require many different tools (existing and novel)

to work together across multiple platforms, programming languages, and architectures. These tools

must work in parallel or sequential pipelines that can be configured and customised by the application

developer. Therefore, standardised execution architectures, such as the UIMA (Unstructured

Information Management Architecture) standard released by OASIS, are a necessity for ensuring the

interoperability and consistent execution of different tools combined in an application. To this end, we

are looking for a student to develop a standards compliant implementation of UIMA in the Smalltalk

programming language and environment, along with compatible implementations of core language

processing tasks (e.g. tokenisation and sentence splitting). If time permits, the student would also

develop adapters, using the Smalltalk-Java Bridge ‘JNIPort’, to the Java implementation, Apache

UIMA, which is not 100% UIMA compliant. (Suitable for Vacation Scholarship)

Key Words: Software Engineering, Natural Language Processing



ACRC: STRATEGIC INFORMATION MANAGEMENT

Cloud Security

Project Summary: Students will work to address emerging security and privacy challenges related to

cloud infrastructure, and its applications and services. This will be achieved by designing solutions to

mitigate malicious attacks, both external and by trusted users (e.g. cloud service provider employees)

to ensure the security and privacy of user data. (Suitable as PhD, Masters or Honours project)

Key Words: Cybersecurity, Cloud security, Cloud privacy

Contact person and details: Dr Ben Martini, Dr Gaye Deegan

E [email protected]; T 8302 5688; URL http://people.unisa.edu.au/Ben.Martini

Collaborative Web search (social search)

Project Summary: Research has shown that people intend to collaborate in various situations.

Nowadays people would like to collaborate through the Web while searching for information. For

example, they often desire to collaborate on search tasks. It is argued that introducing support for

collaboration and communication into information retrieval systems would help users to find

information more effectively. Collaborative information retrieval (CIR) deals with collaboration in

searching for information. The sociality trait of information search has been prominent under Web 2.0.

As an emerging online information search approach, social search not only challenges traditional

theories of information searching but influences people's behaviour as they search information online.

This project explores the characteristics of the collaboration between searchers, and among

searchers, platforms (e.g. social media) and resources available. (Suitable as PhD and Masters

project)

Key Words: Information Systems, Collaborative Information Retrieval, Web Search, Social Media

References:

1. Boydell, O. & Smyth, B. (2010). Social summarization in collaborative Web search. Information

Processing & Management, 46(6), 782-798.

2. Morris, M. R. (2008). A survey of collaborative web search practices. In Proceedings of ACM

Conference on Human Factors in Computing Systems (SIGCHI) (pp 1657–1660). New York:

ACM Press.

3. Mohammad Arif, A. S., Du, J. T., & Lee, I. (2014). Understanding tourists’ collaborative

information retrieval behavior to inform design. Journal of the Association for Information Science

and Technology.

4. Shah, C., & Marchionini, G. (2010). Awareness in collaborative information seeking. Journal of

the American Society for Information Science and Technology, 61(10), 1970-1986.

Contact person and details: Dr Tina Du

E [email protected]; T 8302 5269; URL http://people.unisa.edu.au/Tina.Du

Connecting to knowledge: Accessing information via the Internet by

Project Summary: For the first time, this research project explores the social impact of the Internet

on the life of Indigenous Australians. Such as, what it is Indigenous Australians want and do not want

from information technology, their experience with the Internet and web searching, and the extent that

they interact with the Internet to meet every day needs. The findings would be useful to enable

government agencies, funding bodies and community groups to make evidence-based actions and



http://www.oasis-open.org/committees/download.php/28492/uima-spec-wd-05.pdf

http://pharo.org/

https://uima.apache.org/

https://uima.apache.org/




http://people.unisa.edu.au/Ben.Martini


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Indigenous communities

decisions on the role of the Internet in breaking down barriers and closing the gap of social and

economic isolation of Indigenous Australians.

This project investigates Indigenous People’s engagement with the Internet to meet every day needs

and how the Indigenous Communities will benefit from the use of the Internet. Welcome all potential

applicants from diverse backgrounds. Aboriginal students are more than welcome to apply. (Suitable

as PhD and Masters project)

Key Words: Information systems, internet use, web search, information behaviour, Indigenous people

References:

1. Dyson, L. E. (2004). Cultural Issues in the Adoption of Information and Communication

Technologies by Indigenous Australians. In F. Sudweeks and C. Ess (eds), Proceedings Cultural

Attitudes Towards Communication and Technology 2004, Murdoch University, Australia, pp. 58-

71.

2. Dyson, L. E. & Underwood, J. (2006). Indigenous People on the Web. Journal of Theoretical and

Applied Electronic Commerce Research, 1(1), 65-76.

3. Lilley, S.C. (2008). Information barriers and Māori secondary school students. Information

Research, 13(4) paper 373. [Available at http://InformationR.net/ir/13-4/paper373.html]

4. Meyer, H.W.J. (2009). The influence of information behaviour on information sharing across

cultural boundaries in development contexts. Information Research, 14(1) paper 393 [Available

from 1 March, 2009 at http://InformationR.net/ir/14-1/paper393.html]



Cybersecurity Policy

Project Summary: Cybersecurity has become an increasingly important topic, not only for IT

professionals, but for almost all organisations that utilise IT systems. In this project, students will

explore a contemporary aspect of cybersecurity policy for a mutually agreed upon industry

sector/client. For example, students may choose to investigate the practicality of a particular industry

sector hosting its corporate data using a public cloud service from privacy, security and data

sovereignty perspectives. (Suitable as PhD, Masters or Honours project)

Key Words: Cybersecurity, Information Systems

Contact person and details: Dr Ben Martini, Dr Gaye Deegan


Digital Forensics (including Cloud and Mobile Forensics)

Project Summary: Digital forensics (also known as forensic computing, computational forensics and

computer forensics) is a discipline that is concerned with the acquisition and analysis of digital

evidence. The use of digital forensics can be applied to any crime that involves a digital device

capable of storing electronic/digital information (e.g. in murder investigations where computers, mobile

devices and digital cameras were used). Given the constantly increasing use of ICT in everyday life,

digital evidence is increasingly being used in the courts in Australia and overseas. To reduce the risk

of digital (forensic) evidence being called into question in judicial proceedings, it is important to have a

rigorous methodology and set of procedures for conducting forensic investigations and examinations.

There is a range of digital forensic projects available across a range of different disciplinary bases.

Examples include:

Cloud forensics

Mobile forensics

Hard disk forensics, particularly Solid State Drives (SSDs) forensics

Digital forensic and incident response standards

(Suitable as PhD, Masters or Honours project)

Key Words: Cybersecurity, Digital forensics

References:

1. McKemmish, R 1999, ‘What is forensic computing?’, Trends & Issues in Crime and Criminal

Justice, no. 118 Australian Institute of Criminology, Canberra.

2. Martini, B. and Choo, K-K R 2012, ‘An integrated conceptual digital forensic framework for cloud

computing’, Digital Investigation, vol. 9, no. 2, pp.71-80.

Contact person and details: Dr Ben Martini


Immigrant youth and children

Project Summary: Population is a central issue for any nation, but particularly for one composed

mainly of recent immigrants that is continuing to build itself on immigration. According to the figures

released by the Australian Bureau of Statistics (ABS), as at June 2010, more than one in four people

in Australia were born overseas, with many of these arriving as young adults, youth, and children. In

this project, the student will work with the migrant youth and children in their own settings to

http://informationr.net/ir/13-4/paper373.html

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investigate and understand how they engage with their family, friends, and everyday life around

information and social media and how all of this can be better supported through social services such

as public library services. The knowledge gained from this study will recommend strategies that

librarians can use to help public libraries design better services for immigrant populations by focusing

on what works best for their youth and children. (Suitable as PhD and Masters project)

Key Words: Information Management, Information Behaviour, Information Use, Public Libraries

References:

1. Chu, C. M. (1999). Immigrant children mediators (ICM): Bridging the literacy gap in immigrant

communities. The New Review of Children's Literature and Librarianship, 5, 85-94.

2. Du, J. T. (2014). The information journey of marketing professionals: Incorporating work task-

driven information seeking, information judgments, information use, and information sharing.

Journal of the Association for Information Science and Technology. DOI: 10.1002/asi.23085

3. Katz, I., & Redmond, G. (2009). Review of the Circumstances among Children in Immigrant

Families in Australia. In Innocenti Working Paper - Special Series on Children in Immigrant

Families in Affluent Societies (IWP-2009-12).

4. Khoir, S., Du, J. T., & Koronios, A. (2014). Study of Asian immigrants’ information

behaviour in South Australia: Preliminary results. In Proceedings of the iConference (pp. 682-

689). doi:10.9776/14316.

5. Taylor, J. & H. MacDonald. (1992) Children of Immigrants: Issues of Poverty and Disadvantage,

Bureau of Immigration and Population Research, Canberra.



Information and Communications Technology Leadership

Project Summary: In the turbulent, hypercompetitive business world, the impact of Information and

Communications Technology (ICT) projects on organisational activities is immense; it constantly

modifies the strategies of organisations. IT executives/Chief Information Officers (CIOs) are standing

at the center of these changes. Their role and responsibilities have changed beyond the traditional

technical service role and have grown significantly in importance. In modern day organisations much

more is expected as the role is transformed to that of a valuable business leader. This research area

investigates management and leadership aspects related to ICT executives, especially female ICT

leaders, with a specific focus on the role and responsibilities of the CIO, the challenges they face and

the essential capabilities required of them to bridge the business-IT gap in modern organisations.

(Suitable as Masters or PhD project)

Key Words: ICT Management and Leadership, The role of the CIO

References:

1. Evans, A. 2003. Creating Fusion in the Business-IT relationship: The Organisational Development

(OD) Role of the IT executive. Proceedings of the Conference on “Management challenges of the 21st

century” held in Johannesburg, South Africa. September.

2. Evans, A. 2004. Promoting Fusion in the Business-IT Relationship: A chicken-and-egg situation?

Proceedings of the INSITE conference in Rockhampton, Australia. June.

3. Evans, A. 2005. The Role of Women in ICT – a South African Perspective. Global IT Management

Association’s (GITMA) conference in Alaska. June.

4. Zaaiman, J.J. & Evans, A. 2005. The Role of the CIO as Change Agent in modern Organisations.

Proceedings of the Global IT Management Association’s (GITMA) conference held in Alaska. June.

5. Evans, A. 2006. Leading ICT in South Africa: A unique challenge. ACM SIGCPR, California, USA.

April.

6. Malcolm, R. & Evans, N. 2013. From Business-IT Alignment to Fusion: A framework. European

Conference of Management, Leadership and Governance (ECMLG), Klagenfurt, Austria. 14-15

November.

7. Malcolm, R. & Evans, N. 2013. Business-IT Fusion: Developing a Shared World View. European

Conference of Management, Leadership and Governance (ECMLG), Klagenfurt, Austria. 14-15

November.

Contact person and details: Dr Nina Evans

E [email protected]; T 8302 5070; URL http://people.unisa.edu.au/Nina.Evans

Information Asset Management

Project Summary: The most successful organisations are those that deliver the greatest value to

their clients for the least expenditure of scarce and valuable resources, namely their Financial Assets

(money), Human Assets (people), Physical Assets (property, infrastructure, hardware and software)

and Information Assets (data, information and knowledge). With increased access to information

creating digital disruption and cyber-security exposures on one hand and unprecedented opportunities

on the other, managing data, information and knowledge effectively is business-critical. Managing




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information as a vital business asset enables organisations to improve decision making, mitigate risk,

reduce costs, increase revenue and drive business. Information must not be managed by IT; it must

be managed by the business in a relentless drive to gain tangible business benefit. (Suitable as

Masters or PhD project)

Key Words: Data, Information and Knowledge Management

References:

1. Evans, N. & Price, J. 2012. Barriers to the effective deployment of Information Assets: An

Executive Management Perspective. Interdisciplinary Journal of Information and Knowledge

Management (IJIKM), 7:177-199.

2. Evans, N. & Price, J. 2014. Responsibility and Accountability for Information Asset Management

(IAM) in Organisations. Electronic Journal of Information Systems and Evaluation (EJISE).

3. Evans, N & Price. 2014. Why Organisations Cannot Justify the Effective Management of their

Information Assets. European Conference of Management, Leadership and Governance

(ECMLG), Zagreb, Croatia. 13-14 November.

4. Evans, N. & Price, J. 2015. Enterprise Information Asset Management: The roles and

Responsibilities of Executive Boards. Knowledge Management Research and Practice. March 10,

DOI: 10.1057/kmrp.2014.39.

5. Evans, N. & Price, J. 2015. Information Asset Management Capability: The Role of the CIO. The

21st Americas Conference on Information Systems (AMCIS). Puerto Rico. 13-15 August 2015.

6. Evans, N. & Price, J. 2017. Managing information in law firms: changes and challenges.

Information Research, 22 (1).

Ladley, J. 2010. Making enterprise information management (EIM) work for business: a guide to

understanding information as an asset, New York: Morgan Kaufmann.

(Suitable as Masters or PhD project)

Contact person and details: Dr Nina Evans

E [email protected]; T 8302 5070; URL http://people.unisa.edu.au/Nina.Evans

Mobile and IoT Security

Project Summary: Students will undertake cutting edge research to detect previously unknown

vulnerabilities in embedded Internet of Things (IoT) devices and/or mobile devices. Mobile security

can potentially address a wide spectrum of security aspects, including those related to mobile apps,

operating systems and device firmware, etc. Based on the findings from this research, students will

devise and publish solutions that can be implemented by vendors and/or users to protect against

these vulnerabilities in a practical setting. (Suitable as PhD, Masters or Honours project)

Key Words: Mobile device and app vulnerabilities, Embedded device security

References:

1. Do, Q, Martini, B and Choo, K-K R 2015, ‘Exfiltrating Data from Android Devices’, Computers &

Security, no. 48, pp. 74–91. DOI: http://dx.doi.org/10.1016/j.cose.2014.10.016

2. Do, Q, Martini, B, & Choo, K-K R 2016, ‘A data exfiltration and remote exploitation attack on

consumer 3D printers’, IEEE Transactions on Information Forensics and Security, vol. 11, no. 10,

pp. 2174-2186.

3. D’Orazio, C and Choo, K-K R 2015 ‘A generic process to identify vulnerabilities and design

weaknesses in iOS healthcare apps’, In Proceedings of 48th Annual Hawaii International

Conference on System Sciences (HICSS 2015), pp. 5175–5184, 5–8 January 2015, IEEE

Computer Society Press.

Contact person and details: Dr Ben Martini


Online multitasking (Mobile multitasking)

Project Summary: In the daily life, humans are naturally multitasking beings, who are often either

handing multiple tasks sequentially or in parallel, or executing one task across multiple working

sessions. These phenomena have also been recently observed on the Web environment. Multitasking

is viewed to be important user behaviour in Web/online sessions. Performing multiple tasks (related or

unrelated) and multi-session tasks are two common patterns of multitasking on the Web. In the first

pattern, Web users execute several tasks, related or unrelated, simultaneously and switch between

them; while in the second pattern, users execute a single task spanning multiple online sessions.

There has been a large body of research reporting on the second pattern, including the features and

approaches of multi-session tasks and the corresponding Web browser tools support such as

revisitation functionality and resumption support. However, little research has examined the first

pattern multitasking behaviour in Web search. This project investigates how Web users manage

multiple tasks/topics concurrently and how to present them running in parallel in a browser in such a

way as to make sense to users. Online multitasking on the mobile platform could be an interesting

focus. (Suitable as PhD and Masters project)


http://people.unisa.edu.au/Nina.Evans

http://dx.doi.org/10.1016/j.cose.2014.10.016



Updated 19/06/2017 28 | P a g e

Key Words: Information Systems, Interactive Information Retrieval, Web Search, User Experience

References:

1. Du, J.T. (2011). Cognitive coordinating behaviors in multitasking Web search. In Proceedings of

the 34th International ACM SIGIR Conference on Research and Development in Information

Retrieval (ACM SIGIR), pp.1117-1118.

2. Du, J.T. & Spink, A. (2011). Towards a Web search model: Integrating multitasking, cognitive

coordination and cognitive shifts. Journal of the American Society for Information Science and

Technology, 62(8), 1446–1472.

3. MacKay, B. & Watters, C. (2012). An examination of multisession Web tasks. Journal of the

American Society for Information Science and Technology, 63(6), 1183–1197.

4. Wang Q. & Chang H. (2010). Multitasking bar: Prototype and evaluation of introducing the task

concept into a browser. In Proceedings of the Special Interest Group on Human–Computer

Interaction (SIGCHI) Conference on Human Factors in Computing Systems (pp. 103–112). New

York: ACM Press.



ACRC: WEARABLE COMPUTER

A New Projector Based Augmented Reality Precise CAD-Like Manipulations

Project Summary: Projector-based augmented reality is the projection of virtual information directly

onto and registered to physical objects. Users are able to view this information unencumbered by

technology, such head mounted displays or handheld devices, and they are to interact with physical

object and virtual information simultaneously. Interestingly that much of the physical hardware

(computers, projectors, cameras, and networks) requires existing technologies found in current office

workplaces today. The basic software infrastructure to correctly register the virtual information onto

the physical objects is currently operational. The research investigation into the user interface

techniques is still required to make projector-based augmented reality a useful tool. In particular, there

are a number of problems for a user performing precise manipulation for CAD-like operations.

The project will demonstrate the effectiveness of the user interface methodology by showing its ability

to support industrial activities such as: product design, training for manufacturing, in-situ information

presentation for assembly, layout for confined command and control centres, and home

entertainment. The current development of information for these is with traditional CAD applications.

The techniques developed under this proposal will allow users to interact and perform effective tasks

in a completely new fashion with computers, such as interact with simulated buttons, precise

placement of details on a physical object, presentation of animated instructions on a moving assembly

line, or react to the placement of a user’s hand on the physical object. Currently the best options are

the use of a traditional mouse and simple 3D pointing.

Research question posed by this investigation is as follows: “What are an effective precise user

interface interaction techniques to support tasks in projector-based augmented reality?”

This investigation is critical as there is not an appropriate user interface methodology for projector-

based augmented reality. The current state of the art projector-based augmented reality is simple

freehand drawing and painting, with all the precise manipulation performed with 3D CAD applications.


Key Words: Computer Science, Augmented Reality, ACRC, Wearable Computer Lab

Contact person and details: Professor Bruce Thomas

E Bruce [email protected]; T 8302 3464; URL http://people.unisa.edu.au/Bruce.Thomas

Augmented Reality Intelligent Tutoring Systems

Project Summary: The research aims to develop a platform for building Intelligent Training Systems

(ITS) using Augmented Reality (AR) for improving training on spatial tasks (eg machine maintenance,

object assembly, etc). There has been existing research that shows that constraint based ITS can

significantly help with improving training, and similarly AR has been used to create simple procedural

training systems. However there has been little research that has tried to combine the two fields

together to create Intelligent AR training systems, thus this research will creating a new approach for

intelligent training systems.

The overall research aim is to explore if Augmented Reality (AR) and be combined with Intelligent

Training System (ITS) software to provide a significantly improved training experience on real world

spatial tasks (eg assembly, maintenance, etc) than traditional tools (eg paper manuals, video clips,

etc). We will develop a prototype system that will allow a user wearing an AR head mounted display

(or using a desktop/handheld system) to look at real world objects and see virtual training cues



mailto:Bruce%[email protected]

http://people.unisa.edu.au/Bruce.Thomas

Updated 19/06/2017 29 | P a g e

superimposed over them to help him or her learn how to perform a task in their natural work setting

(eg how to disassemble a real engine). This aim will be achieved through research conducted in four

related areas: (1) Fundamental tracking, interaction, and AR interface techniques, (2) ITS system

development and tools for spatial representation, (3) System integration and demonstration

development, (4) Evaluation and user testing. Underlying all of this work is background research in

each of the areas to ensure that we are using the most recent research approaches and that it is novel

compared to existing methods. (Suitable as PhD project)

Key Words: Computer Science, Augmented Reality, Expert Systems, Intelligent Tutoring

References:

1. Mitrovic, A., Martin, B. Suraweera, P., Zakharov, K., Milik, N., Holland, J., McGuigan, N. (2009)

ASPIRE: an authoring system and deployment environment for constraint based tutors. Artificial

Intelligence in Education, 19(2), 155-188.

2. Henderson, S. J. & Feiner, S. (2009) Evaluating the benefits of augmented reality for task

localization in maintenance of an armored personnel carrier turret. Proc. 8th Int. Symp. Mixed and

Augmented Reality, 135-144.

3. Westerfield, G., Mitrovic, A., Billinghurst, M. (2013) Intelligent Augmented Reality Training for

Assembly Tasks. In: K. Yacef et al. (Eds.): AIED 2013, LNAI 7926, pp.542-551.

Contact person and details: Professor Mark Billinghurst

E [email protected]; T 8302 3747; URL http://people.unisa.edu.au/Mark.Billinghurst

Augmented Reality Teleconferencing

Project Summary: The goal of this project is to explore how Augmented Reality technology can be

used to enhance remote collaboration and teleconferencing, particularly for remote expert assistance

in industry. Augmented Reality (AR) is technology that allows virtual images to be overlaid on the real

world. Currently, audio and video conferencing tools can provide remote technical assistance,

however software such as Skype is typically designed for supporting face-to-face communication and

not task space collaboration, where the goal is showing the user’s workspace. In complex repair tasks

is it more important to see what the user is trying to do, rather than show their face.

Previous research has shown that using a head mounted display with a camera attached can allow a

remote expert to see what a worker is doing and provide effective support. However, there are

limitations with traditional video conferencing when it is used to support task space conferencing, such

as the remote person not being able to annotate the local user’s view, limited support for gesture

input, or being difficult for the remote user to see separate from where the local user is looking. Using

AR can overcome some of these limitations by directly annotating the workers view with virtual cues.

Earlier research has explored various aspects of using AR to improve remote collaboration. It has

shown that sharing video views of the real world, providing remote virtual pointing, using spatial audio,

and shared 3D models overlaid on real objects can all aid remote collaboration. In this project we want

to continue this research, and in particular exploring how AR can be combined with depth sensing

technologies to support very nature gesture collaboration, and the capture and sharing of the users’

environment. (Suitable as PhD project)

Key Words: Computer Science, Wearable Computing, Augmented Reality, Teleconferencing

References:

1. Kim, S., Lee, G., Sakata, N., & Billinghurst, M. (2014, September). Improving co-presence with

augmented visual communication cues for sharing experience through video conference. In

Mixed and Augmented Reality (ISMAR), 2014 IEEE International Symposium on (pp. 83-92).

IEEE.

2. Gauglitz, S., Nuernberger, B., Turk, M., & Höllerer, T. (2014, November). In touch with the remote

world: remote collaboration with augmented reality drawings and virtual navigation. In

Proceedings of the 20th ACM Symposium on Virtual Reality Software and Technology (pp. 197-

205). ACM.

3. Billinghurst, M., & Kato, H. (2002). Collaborative augmented reality. Communications of the ACM,

45(7), 64-70.

4. S. Fussell, L.Setlock, and R.Kraut. 2003. Effects of head-mounted and scene-oriented video

systems on remote collaboration on physical tasks. In Proceedings of CHI '03. ACM, New York,

NY, USA, 513-520.

5. Gurevich, P., Lanir, J., Cohen, B., & Stone, R. (2012, May). TeleAdvisor: a versatile augmented

reality tool for remote assistance. In Proceedings of the SIGCHI Conference on Human Factors in

Computing Systems (pp. 619-622). ACM.




http://people.unisa.edu.au/Mark.Billinghurst



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Deep neural networks for human emotion recognition

Project Summary: Newly developed "deep learning" methods have reignited the field of neural

networks in the last few years. For example, Google DeepMind recently announced the first

computer program that plays the game of Go at human expert level, and this relied on deep learning.

The aim of this project is to design software that learns to robustly recognise human emotions, by

making use of multiple types of sensor data, such as video, still images, and biometrics. It is expected

that the main algorithm to be implemented will be a deep convolutional neural network. It will be based

on the earlier work of Yu and Zhang [1] who have been able to get emotion recognition rates of up to

85% with a neural network technique.

The context of use will be explore if emotional recognition code can be developed that can run in near

real time on live camera video and so provide feedback on user emotion while operating a computer

interface. For example, using the video feel from a laptop camera to monitor the emotions of a person

in front of it. (Suitable for Vacation Scholarship)

Key Words: Computer Science, Wearable Computing, Teleconferencing

References:

1. Ou, J., et al., jamSheets: thin interfaces with tunable stiffness enabled by layer jamming, in

Proceedings of the 8th International Conference on Tangible, Embedded and Embodied

Interaction. 2013, ACM. p. 65-72.

2. Follmer, S., et al., Jamming user interfaces: programmable particle stiffness and sensing for

malleable and shape-changing devices, in Proceedings of the 25th annual ACM symposium on

User interface software and technology. 2012. p. 519-528.

3. Fujimoto, Y., Smith, R. T., Taketomi, T., Yamamoto, G., Miyazaki, J., Kato, H., Thomas, B. H.,

Geometrically-correct projection-based texture mapping onto a deformable object, IEEE

Transactions on Visualization and Computer Graphics (TVCG), , *TO APPEAR*, 2014

4. Smith, R. T., Thomas, B. H., Piekarski, W., Digital foam interaction techniques for 3D modelling,

Proceedings of the 2008 ACM symposium on Virtual reality software and technology, 61-68,

Bordeaux, France, 2008

Contact person and details: Professor Mark Billinghurst, Associate Professor Mark McDonnell


Deformable User Interfaces

Project Summary: Advancing the science of Deformable Surfaces by inventing new smart materials

that can not only capture their changing form through input but can also recognise properties of the

objects they touch such as sharp, dull, curved and planar characteristics. Deformable Surfaces have

great potential to significantly change the way humans interact with computing systems - just as touch

screens have revolutionised the mobile phone and tablet computing fields. Materials and electronics

are beginning to support flexible and stretchable devices, this research will model deformable surface

properties for future applied uses. As soft deformable materials such as foam, silicon rubber and

liquids are enhanced with sensors, a host of novel devices and interaction techniques will be made

possible. This project will investigate the use of smart materials including new physical prototypes and

actuation technologies. (Suitable as PhD project)

Key Words: Computer Science, Augmented Reality

Contact person and details: Dr Ross Smith

E [email protected]; T 8302 5551; URL http://people.unisa.edu.au/Ross.Smith

Disaggregation of Wearable Computation Devices

Project Summary: This project will investigate the disaggregation of wearable computation devices

over different portions of the user’s body. The current trend of mobile and wearable devices is for

them to be self-contained with all the required functionality. Self-contained devices have the

advantage of being able to operate autonomous without the need of other devices. The approach

taken in this project is to enhance wearable computation devices with the aggregation of functionality

from several devices carried by the user. This approach is particularly appropriate for light weight

devices such as head mounted displays that have an absolute maximum size and weight for the user

to wear comfortable and have a fashionable appearance. The project will produce a series of

wearable computational devices to support head mounted displays and watch computing devices in

user interaction, sensing, and device memory. The main goals of the project are to increase the

functionality and reduce the energy consumption of the wearable devices. (Suitable as PhD project)







http://people.unisa.edu.au/Ross.Smith



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Empathic Conferencing

Project Summary: The goal of this project is to conduct research on how wearable computers can

be used to capture and share emotional experiences. In recent years there has been a lot of research

conducted on how wearable computers can be used to create new types of collaborative experiences.

For example, wearable computers such as Google Glass have cameras on them that can be used

to stream video to a remote person and allow them to see what the wearer is seeing. However there

has been much less research on sharing people's emotional experience. In this project we will explore

how simple physiological sensors can be used to capture a user's emotion and then share that with a

remote partner. For example, heart rate and skin conductivity sensors can be used to detect when a

person is feeling excited, and the visual and audio cues could be used to convey that excitement to a

remote collaborator. (Suitable as PhD project)


References:

1. Tan, C. S. S., Luyten, K., Van Den Bergh, J., Schöning, J., & Coninx, K. (2014). The role of

physiological cues during remote collaboration. Presence: Teleoperators and Virtual

Environments, 23(1), 90-107.

2. TAN, C. S. S. (2014). Enabling Empathic Communication in Ubiquitous Computing Environments

to Improve Interaction between People.

3. Datcu, D. On the Enhancement of Augmented Reality-based Tele-Collaboration with Affective

Computing Technology.

4. Cai, Y. (2006). Empathic computing. In Ambient Intelligence in Everyday Life (pp. 67-85).

Springer Berlin Heidelberg.



Enhancing the social dining experience using augmented reality

Project Summary: This project will investigate a novel method of engaging older adults in meaningful

mealtime social interactions through the use of Augmented reality technology. We will develop a virtual dining system that aims to: (1) facilitate interpersonal interactions; (2) elicit positive emotion; and (3) enhance meal consumption in socially isolated older adults. Information collected will inform the design of a larger "remote dining network" that is ripe for commercialisation. This research will be developed in collaboration with our partner, Test Kitchen, a social enterprise aiming to create positive social and emotional dining experiences for older adults. The team will facilitate the development of two virtual dining booths, the essential interactive software and evaluate the effectiveness. It will involve the use of depth cameras to capture gesture based interactions, stereo projection and Microsoft Hololens to enable the experience. (Suitable for honours or PhD).



Face to Face Collaboration Using HoloLens

Project Summary: The Microsoft HoloLens hardware combines a see-through head mounted display

with excellent indoor tracking, and so provides an ideal platform for Augmented Reality. In this project

we want to explore how the HoloLens could be used to enhance face-to-face collaboration.

The project will involve developing an example HoloLens application that will allow two people in the

same room to view and interact with the same virtual content. This will build on earlier work that we

have done in face-to-face AR interaction [1][2]. In addition we will explore novel interaction methods

such as using virtual cues to show where people are looking, and enabling users to see from each

other viewpoints. (Suitable for Vacation Scholarship)


References:

1. Billinghurst, M., & Kato, H. (2002). Collaborative augmented reality. Communications of the

ACM, 45(7), 64-70.

2. Billinghurst, M., Kato, H., Kiyokawa, K., Belcher, D., & Poupyrev, I. (2002). Experiments with face-

to-face collaborative AR interfaces. Virtual Reality,6 (3), 107-121.



Gaze based remote conferencing

Project Summary: For a number of years people have been studying how head worn cameras

(HWCs) and head mounted displays (HMDs) can be used for remote collaboration on physical tasks.

The HWC allows a remote expert to see what the local user is doing, while a HMD can allow the

remote expert to provide Augmented Reality (AR) virtual cues overlaid on the local user’s view of the







Updated 19/06/2017 32 | P a g e

real world to help them complete the task. For example, in a remote maintenance task, workers using

a wearable AR interface were able to reduce their task performance time by up to 30% [1].

In face-to-face conversation gaze provides information about where a person is directing his or her

attention and so it could also be an important cue in remote collaboration. Previous research has

found that sharing gaze between two remote collaborators significantly improved performance on a

desktop visual search task, compared to audio only communication [2]. However there has been little

research conducted on sharing gaze cues from a wearable collaborative system. In this project we

want to explore the effect of adding gaze tracking to wearable systems for remote collaboration.

The work would extend our earlier pilot work in this area [3] and involve the following: Background

research on gaze tracking in collaborative systems, Create a prototype system integrating a HMD,

HMC and eye-tracker, Conduct user studies with a variety of physical tasks, and Write research

report. (Suitable for Vacation Scholarship)


References:

1. Gauglitz, S., Lee, C., Turk, M., Höllerer, T. (2012). Integrating the physical environment into

mobile remote collaboration. In Proceedings of the 14th international conference on Human

computer interaction with mobile devices and services, pp. 241-250.

2. Brennan, S. E., Chen, X., Dickinson, C. A., Neider, M. B., Zelinsky, G. J. (2008). Coordinating

cognition: the costs and benefits of shared gaze during collaborative search. Cognition. 106, 1465–

1477.

3. Masai, K., Sugimoto, M., Kunze, K., Billinghurst, M. (2016) Empathy Glasses. In Proceedings of

CHI 2016, May 7th – 12th San Jose, CA, USA



Spatial Augmented Reality Design Tools

Project Summary: Currently the design of manufactured high-end instrumented facilities (such as

command centres and control panels) is one of working almost entirely in the virtual world. The

physical space and layout of such systems demands high-level 3D spatial visualizations from the

stakeholders. Instead of visualizing a command centre with virtual reality tools or expensive physical

prototypes, this project will explore white painted lightweight wooden objects that would be built to the

external dimensions of the major components of the centre and the details of the workstation will be

projected onto them via large scale augmented reality.

The current process of decision-making is time consuming. A major effort is the externalisation of the

clients’ needs and requirements. Normal practices require a large number design meetings iterating

over concepts that are present as either engineering drawings or 3D static renderings. The use of

animations with fly-throughs and guided tours allows for a more immersive experience, but the clients

lack the tools to manipulate the concept themselves.

This project wishes to investigate a set of novel tools that allows design teams to manage a process of

the clients to manipulate the design concepts. To do this, we will place the clients in physical

environment that emulates the final high-end instrumented facility. The end users will be able to view

the command centre from any vantage point by merely walking. Physical moving the physical

prototypes or manipulating the virtual information projected onto the prototypes can modify the

configuration of workstations or controls on the panels.

To make these tools useful for the manufacturer, this new design methodology must be embedded in

the company’s current design process. Issues of data transfer, operation semantics, workflows, and

process planning will have to be addressed. (Suitable as PhD project)




Storytelling of Big Data

Project Summary: This project is concerned with the development of storytelling tools to allow a user

to develop multimedia-briefing presentations. In essence presentations that provide a non-linear

means of presenting a set of data points and facts to validate a set of augments. The briefing is not a

written document, but an interactive tool to provide a more complete picture of how the data and facts

support a set of conclusions. The order of the presentation is driving by the particular nature of the

information and the recipients of that information. What is unique about this approach is the end users

are able to drill down in real time to expose more detail on demand. Linear text documents do not

support this functionality.

The storytelling tool has three main parts: 1) collection, 2) authoring, and 3) presentation. The

collection phase supports the user in identifying potential important pieces of data and particular facts

to support a particular conclusion. These must be readily available to the user for the construction of





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the final augment. The authoring phase provides the user the ability to construct an interactive

multimedia presentation to justify the conclusions drawn from the data and facts. These presentations

are chosen from the set of styles that best support the types and forms of augments presented for the

particular domain of the user. Because the presentations are stylised from a set known forms of

augments, the tool is able to provide very high-level support to the end user. Final the presentation will

be interactive. This interactive nature of the presentation allows for a non-linear presentation of the

information. The particular people viewing the presentation guides the order and pacing of the delivery

of the information. (Suitable as PhD project)

Key Words: Computer Science, Augmented Reality



User interaction for interactive constraints and spatial augmented reality

Project Summary: This project will investigate the science of human-computer interaction for spatial

augmented reality (SAR) environments into new methodologies that present design prototypes as

virtual/physical (VP) entities that can be presented and manipulated in ways that are not currently

available. This investigation will provide a tight coupling between design tools and VP design

representations, enabling designers to employ 3D constraint specification via novel input techniques

to directly modify VP entities. By crafting, realizing and evaluating a constraint driven AR user

interface for CAD tools, this project aims to enhance users’ spatial reasoning capacity for numerous

design applications. (Suitable as PhD project)


Contact person and details: Professor Bruce Thomas, Dr Ross Smith, Dr Wolfgang Mayer


Virtual Reality Brain Training Tools

Project Summary: This project will investigate the use of simulation systems to support medical

applications. The study will explore how Augmented and Virtual reality systems can be employed to

develop therapy and training applications. Current research has demonstrated positive outcomes in a

diverse set of medical applications. For example, cognitive performance can be improved in

Alzheimer’s patients by employing simulation systems with exercise [1]. The reduction of pain can also

be achieved through the use of immersive Virtual Reality systems during wound care. More recently

the use of a virtual reality system has been demonstrated to alter the pain thresholds for patients

suffering from neck pain [3]. This project will investigate how a set of virtual reality brain training tools

can be developed to further understand aspects of psychology, pain and cognition with the aim of

developing therapy applications. (Suitable as PhD project)

Key Words: Computer Sciences, Simulation Systems, Augmented Reality, Virtual Reality, Health

Sciences

References

1. Anderson-Hanley C1, Arciero PJ, Brickman AM, Nimon JP, Okuma N, Westen SC, Merz ME,

Pence BD, Woods JA, Kramer AF, Zimmerman EA. Exergaming and older adult cognition: a

cluster randomized clinical trial. American Journal of Preventitive Medicine, 42(2):109-19, 2012

2. Hoffman HG, Doctor JN, Patterson DR, Carrougher GJ, Furness, TA III. Use of virtual reality for

adjunctive treatment of adolescent burn pain during wound care: A case report. Pain

2000;85:305-309.

3. Harvie, D. S., Broecker, M., Smith R. T., Meulders, A., Moseley, G. L., Bogus Visual Feedback

Alters Onset of Movement-Evoked Pain in People With Neck Pain, Psychological Science, 385-

392, Vol:26, No:4, Feb 2015



Visualising and Interacting with Large Graphs of Big Data

Project Summary: Current collections of the big data in many cases can be presented as one large

graph. Recent technological advances have produced very large data sets that can be presented as

graphs that allow humans to discover and comprehend previously hidden information. This information

presentation strategy is employed by intelligence agencies that monitor social network data to identify

possible terrorist attacks, by biologists to explore interactions between cell systems, and by engineers

to explore complex software architectures. As the size of the data sets increases exponentially,

currently known visualization techniques fail to present easily understandable data, and the need to

find new methods of information presentation to support informed decision-making is an open

research question. A current open research question is the need for better methods that allow users to

understand and visualise large networks. This project will extend the science of human interaction with

large graphs by developing new paradigms that present entire graphs employing abstract graph layout







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algorithms and novel input techniques. The goal of developing these methodologies is to reduce the

cognitive overhead that is the key limiting aspect of current visualization methodologies.

Some particular issues for visualising and interacting with large graphs are as follows:

When the number of nodes of a graph approaches or exceeds the number of pixels on the

computer monitor, how is the graph presented and how can the user interact with that graph?

How is the major underlying structure of interest presented to the user? This is of particular

interest when multiple graphs are aggregated together.

What are the appropriate methods of visualising and interacting with graphs of known data

sources/types? This question addresses the issue of tailoring tasks and interactions to graphs from

particular data sources. (Suitable as PhD project)






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PART 2: Centre for Applied Mathematics

In pure and applied mathematics to

discover, understand and interpret natural

phenomena and apply mathematics to

important industrial and social problems.

CIAM researchers work with industry on a

broad range of research and consulting

projects including: optimal train control and

train scheduling, crew rostering, assignment

of grain to customers to satisfy orders and

maximise profits, forecasting renewable

energy generation, minerals processing and

management of water catchments.

Director:

Professor John Boland

[email protected]

Updated 19/06/2017 36 | P a g e

PART 2: Centre for Industrial and Applied Mathematics

Accurate numerical solutions for satellite orbits

Project Summary: The equations governing the motion of a satellite in relativistic space-time are

derived from geodesic equations (Misner, Thorne and Wheeler 1973). The equations of motion are

coupled and non-linear which often means standard numerical methods fall short of the mark. This

project will attempt to utilise symplectic integration schemes (Hairer, Lubich and Wanner 2006,

McLachlan 2006) with mathematical software such as Mathematica to visual satellite motion in

relativity. (Suitable as PhD project)

Key Words: Applied Mathematics

References:

1. Hairer, Ernst, Christian Lubich, and Gerhard Wanner (2006). Geometric numerical integration:

structure-preserving algorithms for ordinary differential equations. Vol. 31. Springer Science &

Business Media.

2. McLachlan, I. Robert and G. Reinout W Quispel (2006). Geometric integrators for ordinary

differential equations. In: Journal of Physics A: Mathematical and General 39.19, p. 5251.

3. Misner, Charles W, Kip S Thorne, and John Archibald Wheeler (1973). Gravitation. Macmillan.

Contact person and details: Professor Jim Hill

E [email protected]; T 8302 3530; URL http://people.unisa.edu.au/Jim.Hill

Applied mathematical modelling in nanotechnology

Project Summary: Famous physicist Richard P. Feynman predicted in his historical talk ‘There’s

plenty of room at the bottom’ that the possibility of miniaturization and nano-devices assembling one

atom at a time! And with the recent boom and success in the area of nanotechnology, such prediction

seems within reach. Nanotechnology has shown to be useful in developing future drug delivery and

high performance lithium battery, enhancing structural strength, advancing NEMS, etc. A deeper

understanding of mechanics at the nanoscale is key to better design of nano-devices. In this project

the student will concentrate on classical applied mathematical techniques for problems that would

incur high cost to investigate experimentally or using computational methodologies. (Suitable as PhD

project)


References:

1. B. J. Cox, N. Thamwattana and J.M. Hill, “Mechanics of atoms and fullerenes in single-walled

carbon nanotubes. I. Acceptance and suction energies.” Proceedings of the Royal Society of

London A, 463 (2007) 461-476.

2. B. J. Cox, N. Thamwattana and J. M. Hill, “Mechanics of atoms and fullerenes in single-walled

carbon nanotubes. II. Oscillatory behaviour.” Proceedings of the Royal Society of London A, 463

(2007) 477-494.

3. B. J. Cox, N. Thamwattana and J. M. Hill, “Mechanics of spheroidal fullerenes and carbon

nanotubes for drug and gene delivery.” Quarterly Journal of Mechanics and Applied Mathematics,

60 (2007) 231-253.



Approximation of Convex Sets

Project Summary: It is well known that convex polytopes are not good approximations for smooth

convex bodies, such as balls in d-dimensional space. The traditional polytope approximation of a ball

suffers from the curse of dimensionality problem in high-dimensional space. In contrast,

approximations of the ball by zig-zag sets such as those proposed in Cheang and Barron (2000) and

Arstein-Avidian et al. (2005) achieve much better approximation rates. Cheang and Barron (2000)

showed that a threshold of a linear combination of c(d/E)^ 2 half-spaces is needed to achieve an

accuracy of E for such an approximation. Arstein-Avidian et al. (2005) improved the result to show

that only c(d log(1/E)/E^2) indicators of half-spaces are needed. But their result only holds with high

probability 1 – e^{-cd}. More recently Cheang (2010) used a single-hidden layer perceptron neural

network implanting the ramp sigmoid activation function to approximate the indicator function of a d-

dimensional ball and used c(d/E)^ 2 ramp sigmoids to achieve a relative accuracy of E. The goal of

this project is to improve on the accuracy of the Cheang (2010) result for the approximation with ramp

sigmoids and also to explore ways of sharpening the result of Arstein-Avidian et al. (2005). (Suitable

as PhD project)

Key Words: Mathematics, Approximation Theory, Functional Analysis, Artificial Neural Networks

References:

1. S. Artstein-Avidan, O. Friedland, V. Milman, Geometric applications of Chernoff-type estimates

and a zigzag approximation for balls, Proc. Amer. Math. Soc. 134 (2005) 1735–1742.


http://people.unisa.edu.au/Jim.Hill



Updated 19/06/2017 37 | P a g e

2. G.H.L. Cheang, A.R. Barron, A better approximation for balls, J. Approx. Theory 104 (2000)

183–203.

3. 3.G.H.L. Cheang, Approximation with neural networks activated by ramp sigmoirs, J. Approx.

Theory 162 (2010) 1050-1065.

Contact person and details: Dr Gerald Cheang

E [email protected]; T 8302 0450; URL http://people.unisa.edu.au/Gerald.Cheang

Collision probability modelling for low earth orbit space satellites

Project Summary: With the present day technological progress, military, communicational,

commercial and scientific applications have dominated an impressive number of spacecraft launches.

Today, providing many services from space such as communications, weather forecasts, television,

remote censoring of the environment and navigation have all become an accepted part of daily life.

The increased number of satellites has increased debris in the low earth orbit region (2000km height)

and arising from various explosions and collisions. The [1], US Space Command in Colorado Springs,

has catalogued a total of 9,174 trackable objects in space which have dimensions greater than 10cm,

and of these, 6,313 are considered to be debris, and the rest are believed to be active payloads. The

major and the most recent collision between two intact artificial satellites namely, Iridium 33 and

Kosmos-2251 in low earth orbit occurred on February 10th 2009 which generated almost 2000

individual debris in space. This uncontrollable artificial debris has a significant disturbance on

operational satellites, and therefore calculating collision probabilities with a high degree of accuracy

has become a timely necessity. The scope of this study is to build new models for calculating the

probability of collision between two space objects, and incorporating the assumptions of a number of

existing models [2],[3]. (Suitable as PhD project)


References:

1. Darrin Leleux et al. “Probability-based space shuttle collision avoidance". In: SpaceOps 2002

Conference, p. 50.

2. Russell P Patera.“General method for calculating satellite collision probability". In: Journal of

Guidance, Control, and Dynamics 24.4 (2001),pp. 716{722. ISSN: 0731-5090.

3. Xiao-Li Xu and Yong-Qing Xiong. “A method for calculating probability of collision between space

objects". In: Research in Astronomy and Astro-physics 14.5 (2014), p. 601. ISSN: 1674-4527.



Computational Methods for Modelling of Nonlinear Systems

Project Summary: In the project, we will study theoretical and practical aspects of computational

methods for mathematical modelling of nonlinear systems. A number of computational techniques

will be considered, such as

1. methods of function and operator approximation with any given accuracy,

2. interpolation techniques including a non-Lagrange interpolation,

3. methods of system representation subject to constraints associated with

4. concepts of causality, memory and stationarity,

5. methods of system representation with an accuracy that is the best within a given class of

models,

6. methods of covariance matrix estimation,

7. methods for low-rank matrix approximations,

8. hybrid methods based on a combination of iterative procedures and best operator approximation,

and

9. methods for information compression and filtering under condition that a filter model should

satisfy restrictions associated with causality and different types of memory.

The project represents a blend of new methods in general computational analysis, and specific, but

also generic, techniques for study of systems theory ant its particular branches, such as optimal

filtering and information compression. (Suitable as PhD project)


References:

1. Torokhti and P. Howlett, Computational Methods for Modelling of Nonlinear Systems, Elsevier,

2007.

Contact person and details: Associate Professor Anatoli Torokhti

E [email protected]; T 8302 3812; URL http://people.unisa.edu.au/Anatoli.Torokhti


http://people.unisa.edu.au/Gerald.Cheang




http://people.unisa.edu.au/Anatoli.Torokhti

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Exact solutions of the Einstein field equations

Project Summary: The theory of relativity gives rise to some of the strangest and non-intuitive

phenomenon in the known universe. Black holes, warped space-time and the bending of light around

massive objects are common aspects of the theory. It is not often one hears black holes being

discussed in the same context as the Global Positioning System (GPS). However, they both provide

experimental evidence validating Einstein's theory. The field equations of gravity that describe such

phenomenon are given by non-linear, coupled partial differential equations. This project will analyse

the field equations and derive more realistic solutions (Schmutzer 1980, Stephani et al. 2009) that

describe the gravitational field of the earth more accurately. (Suitable as PhD project)


References:

1. Schmutzer, E. ed., 1980. Exact solutions of Einstein's field equations (Vol. 19). Cambridge:

Cambridge University Press.

2. Stephani, Hans et al. (2009). Exact solutions of Einstein’s field equations. Cambridge University

Press.



Forward and inverse electromagnetic scattering

Project Summary: When a radio wave meets a dense body, the irregular density of the body

contributes to scatter the radio wave in different directions. In forward scattering we try to predict the

wave spread from our knowledge of the body density. In inverse scattering we try to discover the body

density from information about the wave spread. The work involves knowledge of differential

equations. (Suitable for summer or semester-long research project)


References:

1. Integral Equation Methods in Scattering Theory, D. Colton, R. Kress, published by SIAM.

Contact person and details: Dr Jorge Aarao

E [email protected]; T 8302 3741; URL http://people.unisa.edu.au/Jorge.Aarao

Geometry and geometric issues of atomic nanostructures

Project Summary: It is clear from the various structures seen at the nanoscale that the complex self-

interactions of these structures often lead to symmetric configurations. In satisfying an overall

minimum energy constraint, the system often adopts a symmetric structure that shares the energetic

costs of bending and stretching covalent bonds equally to all components in the structure. By

assuming the symmetric configuration, it is possible to reduce fundamentally complex problems of

molecular structure to problems with are more mathematically tractable and thus derive results which

can be confirmed by experiment and simulation. This approach can also be used to predict ideal

systems and novel structures in certain extreme cases. In this project the student will study geometric

models for nanostructures such as nanotubes, cones and spheres (buckyballs) with the aim of

providing more precise predictions of structural parameters like lengths and radii. (Suitable as PhD

project)


References:

1. B. J. Cox, and J. M. Hill, “Exact and approximate geometric parameters for carbon nanotubes.”

Carbon, 45 (2007) 1453-1462.

2. B. J. Cox, and J. M. Hill, “New carbon molecules in the form of elbow-connected nanotori.”

Journal of Physical Chemistry C, 111 (2007) 10855-10860.

3. B. J. Cox, and J. M. Hill, “Geometric structure of ultra-small carbon nanotubes.” Carbon, 46

(2008) 711-713.

4. B. J. Cox, and J. M. Hill, “A variational approach to the perpendicular joining of carbon nanotubes

to plane graphene sheets.” Journal of Physics A: Mathematical and Theoretical, 41 (2008)

125203 (11pp).

5. B. J. Cox, and J. M. Hill, “Geometric model for boron nitride nanotubes incorporating curvature.”




Graphene production, and graphene folding and bubbling

Project Summary: Graphene comprises carbon sheets of one atomic thickness. The production of

graphene that has uniform electrical and mechanical properties is a major technological challenge,

since with present production methods the graphene tends to inherit any flaws or dislocations that are

apparent in the host metallic material. An ideal production method might involve a sequential

technique rather like that used in conventional weaving with a loom. Once graphene is prepared, it

needs to be transferred onto whatever device is being manufactured, which is usually done with a




http://people.unisa.edu.au/Jorge.Aarao



Updated 19/06/2017 39 | P a g e

metal stamp. On being released from the stamp, graphene tends to crumple and stick together

forming folds and bubbles, both of which are highly undesirable. This project will analyze possible

methods for sequential graphene production, and the mathematical modelling of graphene folds and

bubbles. (Suitable as PhD project)


References:

1. B. J. Cox, D. Baowan, W. Bacsa and J. M. Hill, Relating elasticity and graphene folding

conformation, submitted for publication.



Harmonic Analysis: Developing the theory of function spaces on spaces of homogeneous type

Project Summary: In the mathematical field of harmonic analysis, the functions we study have

traditionally been defined on Euclidean spaces R^n. In recent years, there has been much interest in

the new setting where a Euclidean space is replaced by a more general space of homogeneous type:

a set X equipped with a quasi-metric and a doubling measure. This project will focus on developing

the theory of function spaces such as Hardy spaces, Bounded Mean Oscillation, A_p weights and

reverse Holder weights, the relationships between them, and the operators that act on them, on

spaces X of homogeneous type. We will also consider dyadic and multiparameter versions of the

theory. (Suitable as PhD project)

Key Words: Mathematics, Harmonic Analysis

References:

1. P. Chen, J. Li and L.A. Ward (2013), BMO from dyadic BMO via expectations on product spaces

of homogeneous type, Journal of Functional Analysis 265: 2420—2451.

2. J. Li, J. Pipher and L.A. Ward (in press), Dyadic structure theorems for multiparameter function

spaces, Revista Matematica Ibéroamericana.

3. E.M. Stein (1993), Harmonic analysis: real-variable methods, orthogonality, and oscillatory

integrals, Princeton University Press, 1993.

Contact person and details: Associate Professor Lesley Ward

E [email protected]; T 8302 3038; URL http://people.unisa.edu.au/Lelsey.Ward

High precision modelling of satellite orbits

Project Summary: Space based satellite technology is now part of everyday civilian life. With a

steady increase in the number of active satellite constellations, highly accurate orbit prediction models

are required. The current theory of gravity as proposed by Albert Einstein in his general theory of

relativity describes gravity as a manifestation of space-time curvature. Despite experimental evidence,

orbit prediction models are currently designed from a classical framework where the effects due to

relativity are implemented as a modification to classical theory (Ashby 2003). This project will attempt

to design a fully general relativistic orbit prediction model, where the first problem will address the orbit

of a satellite using the well-known Schwarzschild solution (Misner, Thorne and Wheeler 1973).

Extensions can be made to more accurately describe the gravitational field of the Earth using currently

known alternative solutions (Stephani et al. 2009). (Suitable as PhD project)


References:

1. Ashby, Neil (2003). Relativity in the Global Positioning System. In: Living Reviews in Relativity

6.1, p. 1. url: http://dx.doi.org/10.12942/lrr-2003-1.

2. Misner, Charles W, Kip S Thorne, and John Archibald Wheeler (1973). Gravitation. Macmillan.

3. Stephani, Hans et al. (2009). Exact solutions of Einstein’s field equations. Cambridge University

Press.



Modelling methane storage using nano-bottles

Project Summary: The traditional storage of methane involves the gas stored in a high-pressure

environment. This presents environmental hazards for applications requiring a lot of methane, such as

for vehicle fuel, domestic cooking and heating, because of the dangers of explosion. A new storage

mechanism for methane involves nano-bottles, which combines the advantages of a high - pressure

vessel and adsorbents, but requires a lower pressure and thus presents less risk of an accident. In

this project, the student will study models for new storage possibilities for methane using applied

mathematical modelling in nanotechnology. (Suitable as PhD project)


References:

1. O. O. Adisa, B. J. Cox and J. M. Hill, “Encapsulation of methane in nanotube bundles.” Micro and

Nano Letters, 5 (2010) 291-295.




http://people.unisa.edu.au/Lelsey.Ward



Updated 19/06/2017 40 | P a g e

2. O. O. Adisa, B. J. Cox and J. M. Hill, “Encapsulation of methane molecules into carbon

nanotubes.” Physica B, 460 (2010) 88 – 93.

3. O. O. Adisa, B. J. Cox and J. M. Hill, “Packing configurations for methane storage in carbon

nanotubes.” European Physical Journal B, 79 (2011) 177 - 184.

4. O. O. Adisa, B. J. Cox and J. M. Hill, “Modelling the surface adsorption of methane on carbon

nanostructures.” Carbon, 49 (2011) 3212 – 3218.

5. O. O. Adisa, B. J. Cox and J. M. Hill, “Open carbon nanocones as candidates for gas storage.”


6. Y. Chan and J. M. Hill, “Hydrogen storage inside graphene-oxide frameworks.” Nanotechnology,

22 (2011) 305403 (8pp).



Nanoscaled oscillating systems

Project Summary: Nanoscaled structures such as carbon nanotubes and fullerenes undergo atomic

interactions that are described by van der Waals forces. These can lead to extreme accelerations, and

velocities, and in the case of oscillating systems, to ultra-high frequencies in the gigahertz regime. In

terms of creating novel electronic devices, these high frequencies regimes might be important. By

modelling the structures as surfaces with uniform atomic densities and the van der Waals interactions

using a 6-12 Lennard- Jones potential, we can make predictions regarding these systems including

derivation of formulae for the frequency that are often in good agreement with molecular dynamics

simulations. This project examines models to calculate the force to predict the behaviour of various

oscillating systems. (Suitable as PhD project)


References:

1. B. J. Cox, N. Thamwattana and J.M. Hill, “Mechanics of atoms and fullerenes in single-walled

carbon nanotubes. I. Acceptance and suction energies.” Proceedings of the Royal Society of

London A, 463 (2007) 461-476.

2. B. J. Cox, N. Thamwattana and J. M. Hill, “Mechanics of atoms and fullerenes in single-walled

carbon nanotubes. II. Oscillatory behaviour.” Proceedings of the Royal Society of London A, 463

(2007) 477-494.

3. T. A. Hilder and J. M. Hill, “Oscillating carbon nanotori along carbon nanotubes.” Physical Review

B, 75 (2007) 125415-8.

4. N. Thamwattana and J. M. Hill, “Oscillation of nested fullerenes (carbon onions) in carbon

nanotubes.” Journal of Nanoparticle Research, 10 (2008) 665-677.



New methodologies for Nonconvex and Nonsmooth Optimization

Project Summary: Nonconvex and nonsmooth optimization problems (NNPs) are not tractable by

current available techniques. NNPs arise in finance, biology, medicine, and engineering problems, so

it is important to devise new ways to tackle them in their original, nonsmooth/nonconvex formulation. A

fundamental tool for doing this is duality theory, by which we associate with the original problem

(called the primal problem) another problem (called the dual problem). Research in this area will

develop:

a. new kinds of dual problems, by introducing new augmented Lagrangians. The theoretical aim

here is to establish zero duality gap and strong duality for the corresponding duality schemes, and

b. to devise new solution methods for solving the dual problem, exploiting (when possible) the

structure of the problem.

The theoretical aspects of this project rely on modern tools provided by variational analysis in infinite

dimensions. This includes non-smooth optimization, convex analysis, nonsmooth analysis, and

functional analysis. The new methods will be tested on concrete instances to determine which

Lagrangian structure is more convenient for certain types of problems. (Suitable as PhD project)


References:

1. R. S. Burachik, A. N. Iusem, J. G. Melo, The exact penalty map for nonsmooth and nonconvex

optimization, Optimization, vol 64, no. 4, (2015), pp. 717–738.

2. R. S. Burachik, and C. Y. Kaya, A Deflected Subgradient Method Using a General Augmented

Lagrangian Duality with Implications on Penalty Methods, Variational Analysis and a

Generalized Differentiation in Optimization and Control, special issue in honour of Boris

Mordukhovich. Springer Optimization and Its Applications 47 (2010), pp. 109–132.

3. R. S. Burachik, and C. Y. Kaya, An augmented penalty function method with penalty parameter

updates for nonconvex optimization, Nonlinear Anal. 75 (2012), pp. 1158-1167.





Updated 19/06/2017 41 | P a g e

4. R. S. Burachik, On primal convergence for augmented Lagrangian duality, Optimization. 60

(2011), pp. 979–990.

Contact person and details: Associate Professor Regina Burachik, or C. Y. Kaya

E [email protected]; T 8302 5537; URL http://people.unisa.edu.au/Regina.Burachik

E [email protected]; T 8302 3801; URL http://people.unisa.edu.au/Yalcin.Kaya

Singular perturbations in differential equations

Project Summary: The goal is to study the behaviour of solutions to a differential equation, when the

equation itself depends on a parameter. The case of interest is when the parameter vanishes, and

makes the higher derivatives disappear from the equation. Many examples are known, but not a full

general theory. (Suitable for summer or semester-long research project)


References:

1. A hyperbolic approach to elliptic and parabolic singular perturbation problems, Y. Kannai, Journal

d’Analyse Mathematique 59(1) 75-87, January 1992.

Contact person and details: Dr Jorge Aarao

E [email protected]; T 8302 3741; URL http://people.unisa.edu.au/Jorge.Aarao


http://people.unisa.edu.au/Regina.Burachik


http://people.unisa.edu.au/Yalcin.Kaya


http://people.unisa.edu.au/Jorge.Aarao

PART 3:

Institute for Telecommunications Research

The Institute for Telecommunications

Research (ITR) is an internationally

recognised research group specialised in

research and technology development for

wireless communication. This includes both

fixed and mobile, satellite and terrestrial

based applications.

Strong national and international

relationships and collaborations with the

telecommunications business community

ensure our work has a high degree of

relevance to the problems facing the

wireless communications industry.

Director:

Associate Professor Gottfried Lechner

[email protected]

Updated 19/06/2017 43 | P a g e

PART 3: INSTITUTE FOR TELECOMMUNICATIONS RESEARCH (ITR)

ITR: FREE SPACE OPTICAL COMMUNICATIONS

Adaptive Free-Space Optical Communications

Project Summary: Over the last few decades the uptake of FSO transmission has been limited by

attenuation due to cloud and fog, plus scintillation fading cause by small variations in the refractive

index of the atmosphere. ITR has shown, both in theory and practice, that channel coding methods

are able to address the fading issues and provide reliable and high-speed communication

channels. Recently our institute has started research into adaptive transmission methods for FSO

communications. Adaptive methods have been used very successfully in fading RF channels for

many years, but so far there has been little use of this approach in optical communications. Our initial

investigations indicate that significant performance gains are possible in FSO links. HDR research in

this area will develop these adaptive techniques, including dealing with practical issues such as the

need for rapid synchronisation and the power and bandwidth limitations of real transducers. (Suitable

as PhD project)

Key Words: Free space optical communications

Contact person and details: Professor Bill Cowley, Associate Professor Gottfried Lechner

E [email protected]; T 8302 3858; URL http://people.unisa.edu.au/Bill.Cowley

Coding and Signal Processing For Future Fibre-Optical Communications

Project Summary: Optical communications offers many advantages compared to its radio frequency

counterpart. Optical carriers have a much higher carrier frequency, allowing for significantly higher

information bandwidth. Currently, technological advance in optical communications is overwhelmingly

driven by breakthroughs in physics and photonics. As photonics technologies mature, and data rates

increase, higher-order nonlinear physical effects and dispersion in the medium cannot be ignored

(especially for long-haul transmission). Advanced digital coding and signal processing techniques

become increasingly relevant to address these channel impairments. The aim of this project is to

answer questions concerning data transmission over optical channels.

The project will:

- Develop the mathematical tools required for analysis of optical channels

- Develop new coding and modulation techniques for optical communications

( Suitable as PhD project)

Key Words: Information theory

Contact person and details: Associate Professor Terence Chan

E [email protected]; T 8302 3875; URL http://people.unisa.edu.au/Terence.Chan

MIMO and modulations in visible light communications

Project Summary: To efficiently use the radio frequency (RF) spectrum is an important area due to

the scarcity of the limited spectrum bandwidth. Despite the efforts to improve the RF spectrum

efficiency, the data throughput demand has outpaced the development. Optical wireless

communication has shown the potential to bridge the demand gap due to the wide bandwidth

availability of the optical spectrum. The unregulated and easily available bandwidth (over terahertz)

provided by Visible Light Communication (VLC) is one of the main factors that gives these systems an

advantage over the existing radio frequency (RF) communications. To use visible light for data

communications has gained much attention recently and is developing as a viable and beneficial

communication technology, especially for short-range indoor systems. The advent of high-power light

emitting diodes (LEDs) and highly sensitive photo diodes (PDs) and simultaneous use as a source of

lighting and data communication have helped the development of VLC as an attractive as well as

energy-efficient technique for high-speed data communication. This project will investigate novel

approaches to deal with new challenges in VLC, including coding techniques for intensity constraints

in VLC systems, single carrier and multi-carrier modulations, etc. In particular, a Multiple-Input

Multiple-Output (MIMO) system will be developed by using multiple PDs and LEDs. (Suitable as PhD,

Masters, and Vacation Scholarship)


Contact person and details: Dr Siu Wai Ho

E [email protected]; T 8302 3858; URL http://people.unisa.edu.au/SiuWai.Ho


http://people.unisa.edu.au/Bill.Cowley


http://people.unisa.edu.au/Terence.Chan


http://people.unisa.edu.au/SiuWai.Ho

Updated 19/06/2017 44 | P a g e

Positioning by visible light communications

Project Summary: Location-based services are becoming increasingly important. By knowing a

user’s physical location, a mobile device can provide adequate information to the user and support

different mobile applications. For example, we can have navigation applications and

tracking/monitoring applications in our smartphone. To locate a user in outdoor environments, Global

Positioning System (GPS) and cellular-based positioning have been widely used. For indoor

environments, the performance of these systems is degraded because signals are blocked by walls or

infrastructure. Therefore, alternative solutions are needed for indoor positioning. For example,

positioning systems can be built over wireless local area networks (WLANs). However, the accuracy

of these systems depends on whether the indoor environment is complicated or not. The accuracy can

be from one up to several meters.

This project will investigate an indoor positioning system which is cost-effective and provides accuracy

levels within 0.2 meters by using Visible Light Communications (VLC), which is an emerging and

promising research area. The aim of this project is to develop algorithm and system designs for such a

high precision requirement. (Suitable as PhD, Masters, and Vacation Scholarship)




ITR: INFORMATION THEORY

Information theoretic security and privacy

Project Summary: Information theoretic security relies on no assumption on the computational

power of the adversary. Since the seminal work by Shannon in 1949, a lot of important results have

been developed. Recently, we have a breakthrough by showing a new fundamental relationship

between key size and message size. A new concept about the consumption of a secret key has been

developed. This project explores other fundamental questions in this new direction. The results can be

applied to security problems and also the protection of privacy when we use the Internet. (Suitable as

PhD project)




Partial rate region characterisations: new frontiers of information theory

Project Summary: Rate regions define the fundamental limits of applications in different areas,

including data networks, wireless communications, and security systems. However, techniques of

information theory are unable to completely characterise these regions for every application. Our aim

is to develop methods for analysing rate regions that do not rely on complete characterisations. These

methods will revolutionise our understanding of rate regions by bypassing the difficulties of existing

techniques. Outcomes will provide practically relevant properties of rate regions that will enable novel

applications in communications systems. (Suitable as PhD project)




Refinement of fundamental tools in information theory

Project Summary: In information theory, many famous tools or results cannot be applied to

countably infinite alphabets, e.g., strong typicality, Fano’s inequality and one-time pad. It is important

to consider countably infinite alphabets because this is the general case and this usually gives tighter

bounds, faster convergent rates, etc. Recently, we have generalized the aforementioned tools to

countably infinite alphabets due to the observation that entropy is indeed a discontinuous function.

This project aims to generalize more fundamental results in information theory. Students with good

mathematical and analytical skills are preferred.

In information theory, many famous tools or results cannot be applied to countably infinite alphabets,

e.g., strong typicality, Fano’s inequality and one-time pad. It is important to consider countably infinite

alphabets because this is the general case and this usually gives tighter bounds, faster convergent

rates, etc. Recently, we have generalized the aforementioned tools to countably infinite alphabets due

to the observation that entropy is indeed a discontinuous function. This project aims to generalize

more fundamental results in information theory. Students with good mathematical and analytical skills

are preferred. (Suitable as PhD project)












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ITR: NETWORKS, TRANSMISSION AND CODING TOPICS

Adaptive streaming with delay-constraints

Project Summary: In streaming data over wireless channels with delay constraints, the

instantaneous performance is subject to fluctuations of system states such as the queuing traffic and

channel realization. The streaming performance can be improved by adapting the transmission rate

with the instantaneous system states. The project can be divided in two stages. The first stage

focuses on designing and analysing a new coding scheme, namely rate-varying code that is suitable

for adaptive streaming. In the second stage, rate adaptation policy based jointly on the link layer traffic

and the physical layer performance will be developed. (Suitable as PhD project)

Key Words: Networks, transmission and coding topics

Contact person and details: Dr Khoa Nguyen

E [email protected]; T 8302 3362; URL http://people.unisa.edu.au/Dang.Nguyen

Big Data in Cloud Storage

Project Summary: In the era of Big Data, data storage systems storing massive amounts of data

have become an indispensable component of modern networks, cloud computing and network

applications. In a distributed storage system (DSS), data is stored across multiple data centres to

increase reliability against faults and failures of any individual data centre.

Traditionally, data is directly replicated and stored in each data centre. Despite its simplicity, this direct

mirroring approach requires a huge amount of storage capacity in each data centre. Motivated by

network coding, the new generation of distributed storage system will linearly encode the data before

storing, resulting in a significant reduction in the amount of storage needed in each data centre.

Practically, it is of critical importance that a DSS must be efficient, robust and secure. Data in DSS can

be efficiently updated and retrieved. Furthermore, we must ensure that any eavesdroppers should

reveal no information about the data stored in the data centre and that the system can still repair itself

in case of failure even when there are malicious adversaries tampering or jamming the network.

However, the majority of existing work in DSS ignores these efficiency, security and robustness

issues. This project on the other hand aims to fill this gap by using an information-theoretic approach.

We will focus on deriving fundamental limits as well as practical coding schemes that are efficient,

robust and secure. (Suitable as PhD project)


Contact person and details: Associate Professor Terence Chan, Dr Siu Wai Ho


Distributed control and tracking

Project Summary: Classical closed-loop control systems rely on having high-capacity links between

the sensors, controller and actuators. Meeting this requirement is challenging in distributed systems,

especially in controlling over wireless channels. The communication requirements for distributed

control, namely anytime transmission, were established by Anant Sahai in 2001. However, current

practical anytime codes only partially meet these requirements. This project aims at investigating the

impact of these limitations, and developing new communication and control strategies to address

these issues. (Suitable as PhD project)


Contact person and details: Dr Khoa Nguyen


Distributed Transmit Beamforming for Resilient Communications

Project Summary: The basic idea of distributed transmit beamforming is based on the coordination of

transmit antennas in a smart way such that the received signal at the receiver can be combined constructively, leading to gains in system performance (in the context of reducing power consumption, increasing transmission range or data rate, etc). Transmit beamforming also provides potential benefits by reducing interference and by enhancing security via reduction of information leakage to enemies in a particular direction. Beamforming technique can offer fundamentally new capability to tactical communications networks such as military communications. The objective of this project is to analyse, build and demonstrate a distributed transmit beamforming system for radio communications. Students will be guided to do analytical study, incorporating modelling and simulation, for different approaches in beamforming systems. The project requires knowledge in signal processing and communications as well as good knowledge of programming languages such as Matlab or C. (suitable for PhD projects) Key Words: transmit beamforming, distributed system, wireless communications, coding,

optimisation.

Contact person and details: Dr Khoa Nguyen; Associate Professor Gottfried Lechner; Associate

Professor Terence Chan



http://people.unisa.edu.au/Dang.Nguyen







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Fundamental Limits of LPD Communication

Project Summary: In defence and national security, many situations arise where information must be

conveyed in such a way that it either cannot be reliably recovered, or is rendered undetectable by

unauthorised entities. The former scenario is referred to as secure communication – signal detection

is tolerated, but its information content must be undecipherable to all but the intended recipient. The

latter scenario is referred to as low probability of detection (LPD), or covert communication – the

sender cannot even afford its signal to be detected, let alone its information content be

compromised. While over several decades LPD communication has received much attention in the

literature, most of this work has concentrated on solutions based on pragmatic/heuristic

reasoning. Until recently, very little work has been done regarding the fundamental limits of LPD

communications, especially in the context of modern advancements in wireless communication such

as multi-antenna/multi-carrier communication, cognitive radio and software defined radio. Toward this

end, this research project aims to:

- Formulate a generic information theoretic framework applicable to any channel, e.g. AWGN,

binary symmetric, binary erasure, multi-carrier, multi-antenna channels.

- Understand the trade-offs between key design parameters, e.g. signal-to-noise ratio, local

interference, probability of transmission (burst signalling), decoding error probability and detection

probability.

Note that this project will require close collaboration with the Defence Science and Technology (DST)

Group, Edinburgh, South Australia. As such, it is required that potential candidates are Australian

citizens to be eligible for appropriate security clearances. (Suitable as PhD project)


Contact person and details: Dr Nick Letzepis

E [email protected]; URL http://people.unisa.edu.au/Nick.Letzepis

Information theoretic security for networks

Project Summary: Security is an extremely important aspect in modern information technological

infrastructure. Any security breaches to the system can have disastrous consequences, causing

significant financial losses and long-lasting damages. Therefore, it is of critical importance that data

must be stored and transmitted robustly and securely in the networks, against any eavesdropping or

tampering by malicious adversaries. Network coding opens the door to many interesting possibilities

for information security. The use of multiple transmission paths may increase robustness to denial of

service or jamming attacks. It can also provide security against eavesdroppers. This project explores

some of the security implications and advantages of network coding. (Suitable as PhD project)




Network coding for multimedia multicast

Project Summary: Network coding is a recent breakthrough in telecommunications network

research. Some attractive features of network coding include the efficient use of network resources,

higher data throughput rates and increased robustness against network errors. Network coding is

particularly effective in multicast scenarios, where many users require the same data from a single

source. For example, consider streaming multimedia data over the internet from a single source to

multiple users. Investigate the application of network coding principles to the transmission of

multimedia data in telecommunication networks. Of particular interest are situations where users

require multimedia data at different fidelity/resolution levels. For example, some users may require

high-quality video for high-resolution displays, while other users will require low-fidelity video for small

mobile devices. The main purpose is to devise schemes for efficiently transporting multimedia data

from a single source to many users with different fidelity requirements. (Suitable as PhD project)





http://people.unisa.edu.au/Nick.Letzepis





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ITR: SOFTWARE DEFINED RADIO

Distributed beamforming with SDRs

Project Summary: Modern communication systems often include software defined radios (SDRs).

SDRs not only allow flexibility in the selection and modification of communication standards but also

open new possibilities. One aspect is cooperative communications where multiple radio cooperate in

either receiving or transmitting a signal from/to a remove host.

Critical aspects are the protocol between the radio and the remote host and synchronisation between

the radios. The project requires knowledge in signal processing and communications as well as good

knowledge of programming languages such as C++. (Suitable as PhD project)

Key Words: Software defined radio

Contact person and details: Associate Professor Gottfried Lechner

E [email protected]; T 8302 5189; URL http://people.unisa.edu.au/ Gottried.Lechner

ITR: WAVEFORMS AND ALGORITHMS

High speed satellite downlinks

Project Summary: Future earth-observation satellites require gigabit transmission rates in higher

frequency bands. Limitations in radio frequency spectrum call for spectrally-efficient modulation

schemes, which make gigabit data rates particularly challenging.

In this project we will design a next-generation transmission scheme for future Ka- Band gigabit

satellite downlinks, including novel approaches for dealing with channel effects such as group delay,

ripple and non-linear satellite power amplifiers.

Available PhD and Masters projects include high-speed signal processing and coding architectures,

plus real-time signal synthesis and acquisition to allow realistic performance testing and optimisation

with satellite hardware. (Suitable as PhD project)

Key Words: Waveforms and algorithms


E [email protected]; T 8302 5189; URL http://people.unisa.edu.au/ Gottried.Lechner

Second Generation Search and Rescue

Project Summary: The satellite-based Cospas-Sarsat search and rescue system has assisted with

the emergency rescue of more than 35,000 lives worldwide since introduction in 1982.

A second generation of this system is currently under development, promising to significantly improve

detection rate and localisation accuracy. However, in an emergency, the system’s performance is

often compromised due to interference and atmospheric effects, leading to false detections that waste

valuable resources.

Projects in this area aim to provide novel techniques leading to faster, more reliable, more accurate,

and more cost-effective search and rescue operations using techniques like multi-user detection,

beamforming and advanced signal processing algorithms. (Suitable as PhD project)

Key Words: Waveforms and algorithms


E [email protected]; T 8302 5189; URL http://people.unisa.edu.au/Gottried.Lechner






http://people.unisa.edu.au/Gottried.Lechner

PART 4:

Phenomics and Bioinformatics Research Centre

The Phenomics and Bioinformatics

Research Centre (PBRC) aims to enable

fundamental advances in biological science

through the development and application of

mathematical, statistical and computational

techniques.

One of the primary undertakings of the

PBRC is research in biomathematics,

biostatistics and bioinformatics to support

the biological studies being undertaken by

plant scientists in their quest for an

understanding of plant function, particularly

the mechanisms responsible for abiotic

stress tolerance of cereal plants.

The PBRC receives support from

numerous sponsors, including the

Government of South Australia, the

Australian Research Council, the Grains

Research and Development Corporation

and industry investors.

Director:

Professor Stan Miklavcic

[email protected]

Director:

Professor Stan Miklavcic

[email protected]

Updated 19/06/2017 49 | P a g e

PART 4: Phenomics and Bioinformatics Research Centre (PBRC) Controlled drug delivery with multi-layered tablets

Project Summary: In order to control the effects of many illnesses, the steady release of a drug into

the body is necessary. However, a drug (in tablet form) is usually only administered a few times per

day, with each dosage leading to a dramatic increase in the drug concentration within the body,

followed by a slow decrease as the drug is metabolised. Fortunately, it is now possible to manufacture

layered tablets, with the drug concentration and release rate varying between the layers. This results

in a more steady release of the drug into the system, and maintains it at a more constant

concentration within the body. In this project, we will tackle this problem from two directions. First, we

will calculate the rate of drug delivery assuming that we know the concentration of the drug within

each layer and also the rate at which each layer dissolves. Second, we tackle the more difficult

inverse problem: if the required drug delivery rate is known, how could you construct a tablet with a

finite number of layers that would closely replicate the necessary delivery rate. (Suitable as an

honours project)

Key Words: Partial differential equations

Contact person and details: Dr Bronwyn Hajek

E [email protected]; T 8302 3084; URL http://people.unisa.edu.au/Bronwyn.Hajek

Creating nanopatterns by dewetting polymer brushes

Project Summary: Polymer brushes are polymer chains that have been grafted by one end on to a

solid substrate. In the presence of a solvent, the polymer chains are stretched away from the

substrate, however, if the solvent surrounding polymer brushes dries out, the polymer brushes

collapse onto the substrate in a compact layer. Molecular dynamics simulations have shown that as

the brushes collapse, they can form nanopatterns on the substrate, with the type of pattern depending

on the grafting density and the amount of solvent. In this project, we will test the robustness of these

conclusions using partial differential equations, in much the same way as Murray describes the

patterning on mammalian coats (eg leopards and zebras). (Suitable as an honours project)

Key Words: Partial differential equations

References:

1. T Lee, SC Hendy, C Neto, Tunable nanopatterns via the constrained dewetting of polymer

brushes, Macromolecules, 2013, 46(15):6326-6335

2. JD Murray, Mathematical Biology II: Spatial Models and Biomedical Applications, Springer-

Verlag, Berlin, 2003

Contact person and details: Dr Bronwyn Hajek, Dr Marta Krasowska


Deep learning on plant image analysis

Project Summary: Deep learning methods have experienced an immense growth in interest from the

machine learning and computer vision community in recent decade. This is because it has been

successfully applied on a large amount of challenge tasks, such as face recognition, medical image

analysis and automatic language translation. However, there is little research on plant image analysis

using the deep learning methods. This project is dedicated to developing an automatic deep learning-

based algorithm to have the biological traits (such as leaf coverage, spikes detection and tiller

numbers) from the plant images. (suitable for honours or MSc student)

Key Words: Deep learning, machine learning, image processing, image-based plant phenotyping

Contact person and details: Dr Zhi Lu, Dr Jinhai Cai

E [email protected]; URL http://people.unisa.edu.au/Zhi.Lu

Mathematical models for microelectromechanical machines

Project Summary: Microelectromechanical machines are increasingly being used as sensors and

actuators. At present, their performance is limited due to issues with contamination and friction. In this

project, we will develop a mathematical model to investigate the mechanisms which govern the

interactions in these devices. In particular, we will model the surface forces within these devices and

investigate the use of liquid lubricants, combined with specially designed coatings. (Suitable as PhD

project)

Key Words: Applied math modelling, Physical Chemistry

Contact person and details: Dr Bronwyn Hajek, Professor Jim Hill, Dr Marta Krasowska, Associate

Professor David Beattie



http://people.unisa.edu.au/Bronwyn.Hajek




http://people.unisa.edu.au/Zhi.Lu



Updated 19/06/2017 50 | P a g e

Modelling of fluid and solute transport in non-uniform, periodic capillaries

Project Summary: The flow of fluids and transport of suspending particles in capillaries has attracted

a lot of experimental and theoretical interest in recent years. The interest is partly inspired by the

potential for commercial exploitation in the area of microfluidics and nanofluidics applications in

chemical and pharmaceutical industries. However, inspiration also comes from a desire to understand

a range of natural phenomena, such as arise in plants. We have an interest in extending our recent

efforts to model fluid flow and particle transport in periodic tubes to more general tube conditions, on

the one hand, and considering more detailed (perturbation or asymptotic) analyses in simpler cases,

on the other. (Suitable as PhD project)

Key Words: Applied mathematics/mathematical modelling

References:

1. N. Islam, B. Bradshaw-Hajek, S.J. Miklavcic, L.R. White (2015) “The onset of recirculation flow in

periodic capillaries: geometric effects”, European Journal of Mechanics - B/Fluids, 53, pp119-128.

2. N. Islam, S.J. Miklavcic, B. Bradshaw-Hajek, L.R. White (2016) “Convective and diffusive effects

on particle transport in asymmetric periodic capillaries”, Physical Review E (submitted).

Contact person and details: Professor Stanley Miklavcic, Dr Bronwyn Hajek

E [email protected]; T 8302 3788; URL http://people.unisa.edu.au/Stan.Miklavcic

Modelling of salt and water transport in plants

Project Summary: Abiotic stresses such as high salt levels in soils can severely affect cereal crop

health, development and grain yield. Currently, high salinity affects two-thirds of Australian cereal

crops. To increase plant salinity tolerance it is necessary to manipulate the transport of ions (e.g.,

sodium and chloride) through a plant. However, this requires knowledge about how ion transport

through a plant occurs. In particular, it is necessary to identify the key points in this transport pathway

to target in order to generate a salt-tolerant cereal variety. For example, is targeting the initial influx of

ions from the soil the best method for increasing plant salinity tolerance, or should more effort be

directed towards increasing the compartmentalization of ions in the shoot? None of the existing

models of water and solute transport in plants are currently suitable for analysing the transport of ions.

This project aims to develop detailed mathematical models of water and solute transport through plant

organs and tissues, which will be compared with physiological measurements of fluxes and

accumulated ion concentrations. The overall aim is to aid understanding of the biophysical

mechanisms and processes responsible for increasing plant salinity tolerance. It is envisioned that the

results will help guide plant geneticists and plant breeders in their search for specific genetic traits that

enhance a plant's ability to tolerate salinity. (Suitable as PhD project)


References:

1. K. Foster and S.J. Miklavcic. “Mathematical modelling of the uptake and transport of salt in plant

roots”, J. Theoretical Biology, 336, pp132-143.

2. K. Foster and S.J. Miklavcic. “On the competitive uptake and transport of ions through

differentiated root tissues”, J. Theoretical Biology, 340, pp1-10.

3. K. Foster and S.J. Miklavcic. “Toward a biophysical understanding of the salt stress response of

individual plant cells”, J. Theoretical Biology, 385, pp130-142.

Contact person and details: Professor Stanley Miklavcic


Modelling of surface forces in ionic liquids

Project Summary: Ionic liquids or molten salts are very highly concentrated salts in a fluid state.

Such systems feature prominently in many chemical industry processes. However, their behavior has

not been completely nor adequately quantified. In particular, how ionic liquids influence the interaction

between macroscopic surfaces is not known, with conflicting experimental studies confusing the

picture. This is a theoretical project aimed at developing a mathematical model to describe the forces

between macroscopic surfaces in the presence of an intervening ionic liquid. The project involves the

application of advanced statistical mechanical models to help understand how ionic liquids influence

the forces. We shall compare the results with published data as well as new in-house surface force

measurements. (Suitable as PhD project)


Contact person and details: Professor Stanley Miklavcic, Dr Jason Connor



http://people.unisa.edu.au/Stan.Miklavcic





Updated 19/06/2017 51 | P a g e

Sequential data analysis by integrating hidden Markov modelling with domain knowledge

Project Summary: Hidden Markov Models (HMMs) are statistical models of sequential data that

have been used successfully in many applications in artificial intelligence, pattern recognition and

modelling of gene sequences. This project aims at developing new statistics modelling approach to

integrate conventional HMMs with experts’ prior knowledge (domain knowledge) to improve the

capacity and the accuracy of the HMMs.

Previous works on HMMs focus on how to capture the statistic information from the sequential data

and the relationships between events in time sequences. In this approach, we will develop new

structure for HMMs, likely the multilayered and coupled structure, to represent domain knowledge,

structure information as well statistic information into individual models. The developed novel HMMs

will be applied to biology and health science. (Suitable as PhD project)

Key Words: Image processing, computer vision and machine learning

References:

1. J. Cai and Z.Q. Liu, “Integration of structural and statistical information for unconstrained

handwritten numeral recognition,” Pattern Analysis and Machine Intelligence, IEEE Transactions

on 21 (3), 263-270.

2. J. Cai and Z.Q. Liu, “Pattern recognition using Markov random field models”, Pattern

Recognition 35 (3), 725-733, 2002.

3. J. Cai, D. Ee, R. Smith, “Image Retrieval Using Circular Hidden Markov Models with a Garbage

State”, IVCNZ 2007, 115-120.

4. J. Cai, “Enhanced HMM for the Recognition of Sigma70 Promoters in Escherichia coli”, Digital

Image Computing: Techniques and Applications (DICTA), 2008, 46-51.

Contact person and details: Dr Jinhai Cai, Professor Stanley Miklavcic, Dr Hamid Laga (Murdoch

University)

E [email protected]; T 8302 5533; URL http://people.unisa.edu.au/Jinhai.Cai

Symmetry methods for nonlinear partial differential equations

Project Summary: In this project we will apply a number of symmetry methods to determine

solutions of some well-known nonlinear ordinary and partial differential equations, such as those

arising in general relativity, acoustics, finance, environmental and biological situations, and industrial

processes. In this project we will exploit the use of Lie point (classical) symmetry analysis and other

modern approaches to solving PDEs. Lie point symmetry analysis provides a powerful method for

finding groups of transformations which enables one to transform the ODE or PDE to an equivalent

equation of simpler form. In this way, exact analytical and numerical solutions may be found.


Key Words: Applied Mathematics, partial differential equations

Contact person and details: Dr Bronwyn Hajek, Professor Jim Hill



http://people.unisa.edu.au/Jinhai.Cai



Updated 19/06/2017 52 | P a g e

PART 5: Future Industries Institute

The School also has strong links with the

Future Industries Institute (FII) which is

the University of South Australia’s new

multi-million dollar Institute. FII focuses

on building knowledge and capacity in

core future industries and develops the

University’s internationally competitive

research capacity across four key

strands:

• Minerals and Resources engineering

• Energy and advanced manufacturing

• Environmental science and

engineering

• Biomaterials engineering and

nanomedicine.

FII focuses on creating high value,

knowledge intensive alternatives

underpinned by unique skill bases,

infrastructure technology solutions and

collaborative research relationships. It

brings together the University’s world-

class strengths and encourages

researchers to blur the boundaries and

build new relationships between industry

and academia.

Director:

Professor Emily Hilder

[email protected]

Updated 19/06/2017 53 | P a g e

PART 5: Future Industries Institute (FII) Controlling Nanopatterns from Polymer Brushes.

Project Summary: Nanopatterned polymer surfaces are important for applications with controlled

mechanical properties. Polymer brushes grafted onto a solid substrate can, depending on polymer

interaction with the solvent, either stay extended or collapse. By controlling the nature of the solvent

as well as its amount, we can control the patterns formed by polymer brushes, and the hence

mechanical properties of such layers.

The properties of polymer layers grafted on a solid surface will be studied using atomic force

microscopy (AFM). AFM is a powerful characterization tool for materials science, capable of revealing

surface structures with superior spatial resolution (nanometer scale) as well as mechanical properties

(softness, adhesion, deformation) of such surfaces. (Suitable as Honours, MSc or PhD project)

Key Words: Advanced Materials, Applied Mathematics

References:

1. T. Lee, S.C. Hendy, C. Neto, Tunable nanopatterns via the constrained dewetting of polymer

brushes, Macromolecules, 2013, 46 (15), pp 6326-6335

Contact person and details: Dr Marta Krasowska, Dr Bronwyn Hajek

E [email protected]; T 8302 3084; URL http://people.unisa.edu.au/Marta.Krasowska

Thin Films from Ionic Liquids

Project Summary: When a liquid drop contacts a solid surface a thin film can spread ahead of the

bulk liquid at the three phase contact line region. These films are referred to as precursor films. They

are formed when intermolecular forces of attraction between solid and liquid are strong enough to

induce spontaneous spreading. Spreading patterns in such films are influenced by the nature of the

liquid (e.g. its volatility) and the solid.

The morphology and extent of precursor films formed by ionic liquids will be studied by atomic force

microscopy (AFM), while elemental surface analysis will be probed with X-ray photoelectron

spectroscopy (XPS). (Suitable as Honours, MSc or PhD project)

Key Words: Advanced Materials, Applied Mathematics

References:

1. D. A. Beattie, R. M. Espinosa-Marzal, T. T. M. Ho, M. N. Popescu, J. Ralston, C. J. E. Richard,

P. M. F. Sellapperumage, M. Krasowska, Molecularly-Thin Precursor Films of Imidazolium-

Based Ionic Liquids on Mica, J. Phys. Chem. C, 2013, 117 (45), pp 23676–23684

Contact person and details: Dr Marta Krasowska, Dr Bronwyn Hajek, Associate Professor David

Beattie

E Marta.Krasowska @unisa.edu.au; T 8302 6861; URL http://people.unisa.edu.au/Marta.Krasowska


http://people.unisa.edu.au/Marta.Krasowska


http://people.unisa.edu.au/Marta.Krasowska

Updated 19/06/2017 54 | P a g e

unisa.edu.au/itms

Email: [email protected]

Telephone: +61 8 8302 3582

The information provided in this publication is for general information

only, and the University of South Australia makes no representation

about the content, suitability, accuracy or completeness of this

information for any purpose. It is provided “as is” without expressed or

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