do the impossible · our research groups explore energy efficiency via low-voltage design...

D O T H E

I M P O S S I B L EE V E R Y D A Y

I L L I N O I S C O M P U T E R S C I E N C E

G R A D U AT E P R O G R A M S

F A C T S & F I G U R E S

90 Faculty

1,286 Graduate Students

1,740 Undergraduate Students

14,040 Alumni

$32.3 Million in Research Expenditures in 2017

Birthplace of Mosaic, the World’s First Popular Web Browser, and the LLVM Compiler Infrastructure

University of Illinois recieved more NSF Funding then any otherUniversity in 6 out of the last 8 years

College of Engineering Ranked #13 in Academic Rankings of World Universities in Engineering

ILLINOIS CS ranked #5 in the U.S. News & World Report Graduate School Rankings

We’re a big campus — Big 10, to be exact — with $642 million spent on research and development in a typical year. We have 15 schools and colleges, including our internationally known Grainger College of Engineering, where the Department of Computer Science resides. This substantial breadth offers many opportunities for CS graduate students to conduct collaborative groundbreaking research that can impact not only computing but medicine, business, the arts, media, or whatever defines your research and passion. Together we can do the impossible every day.

☐ A dynamic and stimulating research culture with nearly 150 potential faculty advisors, covering 11 research areas and every sub-area in between.

☐ A top-five CS graduate program and top-ranked programs on campus in computer engineering, information science, physics, psychology, and engineering.

☐ Flexible programs of study enabling graduate students to craft a learning experience that best fits their passions, interests, and goals.

☐ A culture of collaboration where the best minds tackle a myriad of 21st-century problems by developing cutting-edge data science techniques and harnessing the power of petascale computing.

☐ Thousands of creative and driven alumni who are entrepreneurs, educators, and technical visionaries. Companies who have been founded or led by Illinois Computer Science graduates are among the biggest names in the high-tech arena, including C3 IoT, Match.com, Microsoft, Netscape, PayPal, YouTube, and Yelp.

I L L I N O I S C O M P U T E R S C I E N C E O F F E R S . . .

I L L I N O I S C O M P U T E R S C I E N C E

G R A D U AT E P R O G R A M S

C S G R A D U A T E P R O G R A M S T E A M

JOHN C. HART Professor & Director of Online Programs

NANCY M. AMATOAbel Bliss Professor & Department Head

BRIAN BAILEYProfessor & Director of Graduate Programs

ROBIN KRAVETZProfessor & Associate Director of Graduate Programs

VIVEKA P. KUDALIGAMACoordinator of Graduate Programs

KARA MACGREGOR

Senior Graduate Admissions/Advisor

MAGGIE METZGER CHAPPELLGraduate Admissions/Advisor

DESIREE MARMON

Online Graduate Admissions/Advisor

CHRISTINE J. MARTINEZOnline Graduate Admissions/Advisor

Graduate Programs Office / 1210 Thomas M. Siebel Center, 201 N. Goodwin Avenue / Urbana, IL 61801

G R A D U A T E P R O G R A M S / 1

F O R A D M I S S I O N S Q U E S T I O N S ,P L E A S E C O N T A C T U S

On-Campus Programs: Online Programs: [email protected] [email protected]. edu

Learn from and work with some of the best CS faculty in the world. Our 90 INTERNATIONALLY RECOGNIZED FACULTY include 15 ACM Fellows, 17 IEEE Fellows, 8 Sloan Research Fellows, and 36 NSF CAREER Award winners. And our faculty generated $32.3 million in research expenditures in 2018.

Architecture, Compilers, and Parallel Computing

—Artificial Intelligence

—Bioinformatics and

Computational Biology

Computers and Education—

Database and Information Systems

—Interactive Computing

—Programming Languages,

Formal Methods, and Software Engineering

Scientific Computing—

Security and Privacy

Systems and Networking—

Theory and Algorithms

F R O M A T O P - 5 P R O G R A M W I T H R E S E A R C H I N :

The demand for computer science education has exploded because computing underpins just about every aspect of modern life. The arts, science, business, medicine, and engineering all benefit from the computational power, modeling, and thinking found in computer science. Our students and faculty are bringing their expertise to bear on many of society's most challenging problems. Illinois Computer Science has a global reputation for developing revolutionary technology—where groundbreaking research addresses real-world problems.

W O R L D - C L A S SF A C U LT Y

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R E L A T E D R E S E A R C H E F F O R T S & G R O U P S

A R C H I T E C T U R E , C O M P I L E R S , A N D PA R A L L E L C O M P U T I N G

As we approach the end of Moore’s Law, and as mobile devices and cloud computing become pervasive, all aspects of system design—circuits, processors, memory, compilers, programming environments—must become more energy efficient, resilient, and programmable. ☐ Comp-Gen Initiative in the Carl R.

Woese Institute for Genomic Biology

☐ Midwest Big Data Hub

☐ National Center for Supercomputing Applications

☐ The LLVM Compiler Infrastructure

☐ Parallel Computing Institute

Sarita Adve Computer Architecture, Parallel Computing, Memory Systems, Domain-Specific and Heterogeneous Systems, Resiliency, Approximate Computing

Vikram Adve Compilers, Parallel Computing, Heterogeneous Parallel Systems, Hardware-Software Codesign, Edge Computing

Nancy M. AmatoParallel Algorithms and Libraries, Parallel Graph Algorithms, Performance Modeling

Christopher FletcherArchitectures for Security and Machine Learning

William Gropp Programming Models and Systems for Parallel Computing

Laxmikant KaleLarge-Scale Parallel Systems; Runtime Systems, Tools, and Frameworks for High-Performance Computing

Klara NahrstedtQuality of Experience, Tele-Immersion, Multi-View Visualization, Embedded Sensors, Distributed and Parallel Systems

Luke OlsonParallel Numerical Algorithms, Performance Modeling

David PaduaCompiler Techniques for Parallel Computing

Lawrence RauchwergerParallel Computing, Compilers, Parallel Libraries, High Performance Computing, Parallel Architecture, Exascale Computing

Marc SnirLarge-Scale Parallel Systems, Algorithms, Libraries

Edgar SolomonikHigh-Performance Computing, Communication Cost Analysis, Tensor Computations, Quantum Simulation

Josep TorrellasParallel Architectures, Power-and Reliability Aware Hardware/Software Architectures

C S F A C U LT Y A N D T H E I R R E S E A R C H I N T E R E S T S


Our research groups explore energy efficiency via low-voltage design techniques, specialized hardware accelerators, adaptive runtime techniques in high performance computing, efficient memory architectures for heterogeneous mobile systems, novel architectures for exascale systems, and other projects. We examine resilience through tolerating variation during chip fabrication, failure-tolerant processor architectures, scalable resilience protocols, and automated software debugging and recovery techniques. We explore programmability through architectural support for synchronization, automatic parallelization and vectorization, performance-portability for heterogeneous mobile systems, high-performance implementations of scripting languages, and highly scalable parallel run-time systems.

In addition to collaborating with major companies, our software artifacts like LLVM and Charm++ are widely used in industry, government labs, and academic research.



Nancy M. AmatoRobot Motion and Task Planning, Multi-Agent Systems, Crowd Simulation

Kevin C. Chang Machine Learning, AI Applications, Data Management Support for AI

Margaret Fleck Computational Linguistics, Programming Language Tools

David A. Forsyth Computer Vision, Object Recognition, Scene Understanding

Jiawei HanMachine Learning, Natural Language-Based Text Analysis, Text Summarization

Kris Hauser Motion Planning, Optimal Control, Integrated Planning and Learning, Robot Systems

Julia Hockenmaier Natural Language Processing, Computational Linguistics

Derek Hoiem Computer Vision, Object Recognition, Spatial Understanding, Scene Interpretation

Heng JiNatural Language Processing, especially on Information Extraction and Knowledge Base Population, as well as its Connections with Computer Vision and Natural Language Generation

Nan Jiang Reinforcement Learning, Machine Learning, Sample Complexity Analyses

Karrie Karahalios Human-Computer Interaction for Machine Learning, AI Explainability

Sanmi KoyejoMachine Learning, Neuroimaging, Biomedical Imaging

Steven M. LaValleRobotics, Motion Planning, Virtual Reality

Svetlana Lazebnik Computer Vision, Scene Understanding, Visual Learning, Vision and Language

Bo Li Secure Machine Learning, Robust Learning

Jian Peng Machine Learning and Optimization

Paris Smaragdis Machine Learning for Audio, Speech, and Music; Signal Processing; Source Separation; Sound Recognition and Classification

Matus Telgarsky Machine Learning

☐ Beckman Institute for Advanced Science and Technology

☐ Natural Language Processing Group

☐ Speech and Language Engineering Group

A R T I F I C I A L I N T E L L I G E N C E

The study of systems that behave intelligently, artificial intelligence includes several key areas where our faculty are recognized leaders: computer vision, machine listening, machine learning, and natural language processing.

Computer vision systems can understand images and video, for example, building extensive geometric and physical models of cities from video, or warning construction workers about nearby dangers. Natural language processing systems understand written and spoken language; possibilities include automatic translation of text from one language to another, or understanding text on Wikipedia to produce knowledge about the world. Machine listening systems understand audio signals, with applications like listening for crashes at traffic lights, or transcribing polyphonic music automatically. Crucial to modern artificial intelligence, machine learning methods exploit examples in order to adjust systems to work as effectively as possible.



Nancy M. AmatoModeling Molecular Motions, Protein Folding, Protein/Ligand Binding

Mohammed El-Kebir Bioinformatics, Cancer Genomics, Cancer Phylogenetics, Phylodynamics, Phylogeog-raphy, Information Visualization

Jiawei Han Mining Biological Text, Biological Named Entity and Relation Extraction

Jian Peng Bioinformatics, Protein Function and Structure, Systems Biology, Machine Learning and Optimization

Saurabh Sinha Bioinformatics, Genomics, Modeling, Sequence Analysis, Machine Learning, Probabilistic Methods, Cancer, Behavior

Tandy Warnow Graph Algorithms, Statistical Estimation, Heuristics for NP-Hard Optimization Problems, Phylogenomics, Metagenomics, Multiple Sequence Alignment, Historical Linguistics

ChengXiang Zhai Intelligent Biomedical Decision Support Systems, Analysis of Electronic Medical Records, Biomedical Literature Retrieval and Mining

☐ Carl R. Woese Institute for Genomic Biology

☐ Carl Illinois College of Medicine

☐ Comp-Gen Initiative in the Carl R. Woese Institute for Genomic Biology

☐ KnowEnG, an NIH Center for Excellence for Big Data to Knowledge in the Carl R. Woese Institute for Genomic Biology



Our researchers work on core computational biology-related problems, including genomics, proteomics, metagenomics, and phylogenomics. We develop novel techniques that combine ideas from mathematics, computer science, probability, statistics, and physics, and we help identify and formalize computational challenges in the biological domain, while experimentally validating novel hypotheses generated by our analyses.

We are developing algorithms with improved accuracy for large-scale and complex estimation problems in phylogenomics (genome-scale phylogeny estimation), multiple sequence alignment, and metagenomics. We are exploring gene regulation—developing advanced techniques to predict the diverse function of noncoding parts of DNA and to relate interspecies and interpersonal differences in DNA to differences in the organism’s form and function. We work broadly in the development of machine learning techniques for computational biology, with research spanning the areas of molecular and structural biology; networks and systems biology; and molecular mechanisms of human disease.

B I O I N F O R M A T I C S A N D C O M P U T A T I O N A L B I O L O G Y




Abdussalam Alawini Active Learning in Large Classrooms, Teamwork and Collaboration, Computer-Based Assessment, Instructional Technologies

Lawrence Angrave Success Factors of Underrepresented Students in Online Courses, Universal Access, Crowd-Based Course Curation

Mattox BeckmanProcess-Oriented Guided Inquiry Learning, Training Graduate Teaching Assistants, Scalable Education, Semantics Based Autograders

Geoffrey ChallenTechnology to Improve Classroom Interactivity and Outcomes, Data-Driven Approaches to Teaching and Learning

Neal Davis Incentivizing Productive Student Behaviors, Open Source Curricula, Assessment, Learning Analytics

G. Carl EvansOutcomes Assessment

Wade Fagen-UlmschneiderData Discovery, Social Media, Open-Ended Creative Assessments

Elsa GunterScalable Education, Automated Interactive Assessment, Blended Learning

John Hart Learning at Scale

☐ Academy for Excellence in Engineering Education

☐ Illinois Learning Analytics

☐ Office for Mathematics, Science, and Technology Education

Computing has a large and growing impact on education. It is improving classroom interactivity, increasing accessibility, facilitating personalized learning inside and outside the classroom, and providing a platform for exploring fundamental questions about how people learn.

C O M P U T E R S A N D E D U C A T I O N



Geoffrey HermanHow Students Learn Computing, Teaching at Scale, Assessing Student Learning

Eric ShafferTeaching at Scale, Outcomes Assessment, Learning Analytics

Mariana SilvaTeaching at Scale, Assessment, Collaborative Learning, Online Learning Platforms

ChengXiang Zhai Intelligent Education Systems, Scalable Education, Applications of Data Science in Education

Craig Zilles Learning Analytics, Pedagogy, Computer-Based Testing, Assessment, Asynchronous Exams, Item Generation, Concept Inventories, Plagiarism Detection

At the same time, demand for computer science education is skyrocketing world-wide. Reaching larger and more diverse audiences requires both understanding how people learn computer science and creating best practices for teaching specific computing topics.

Our faculty study broadly in both of these facets of computers and education. We build new systems, run them at scale, and design interfaces and study the human impacts of technology in the classroom. We gather and analyze data about student behavior to better understand the learning process using both data science techniques and qualitative research.


Abdussalam Alawini Data Provenance, Scientific Data Management, Data Citation, Workflow Management, Machine Learning

Kevin C. Chang Data Mining, Database Systems, Information Retrieval, Web Search/Mining, Social Media Analytics

Jiawei Han Data Mining, Database Systems, Information Retrieval, Web Search/Mining, Social Media Analytics

Heng JiNatural Language Processing, especially on Information Extraction and Knowledge Base Population, as well as its connections with Computer Vision and Natural Language Generation

Yongjoo ParkDatabase Systems, Big Data Analytics, Approximate Computing, Machine Learning for Systems

Hari Sundaram Network Analysis, Behavioral Modeling, Applications of Game Theory

Hanghang Tong Data Mining, Network and Graph Mining

ChengXiang Zhai Intelligent Information Systems, Information Retrieval, Data Mining, Big Data Applications

The rapid growth of big data creates unprecedented demand and opportunities for developing powerful intelligent information systems that help people manage and extract knowledge from data.

Our faculty work on a wide range of research problems, tackling the many challenges associated with developing such intelligent systems and their applications. Research includes helping people search and find relevant data and information; mining massive amounts of heterogeneous data sets to discover actionable knowledge; optimizing the entire workflow of data access, analytics, and exploration; and analyzing large social networks and to optimize human-computer collaboration centered on data.

Our faculty work closely with industry, and many of our algorithms are used in a wide range of information system applications, especially in database and data analytics systems, data mining systems, search engines, and web information service systems.


☐ Comp-Gen Initiative in the Carl R. Woese Institute for Genomic Biology

☐ Data Analytics Subprogram in the Advanced Digital Sciences Center

☐ Information Network Academic Research Center

☐ KnowEnG, an NIH Center for Excellence for Big Data to Knowledge in the Carl R. Woese Institute for Genomic Biology


D A T A B A S E A N D I N F O R M A T I O N S Y S T E M S




Brian P. Bailey Human-Computer Interfaces, Design Thinking, Creativity, Crowdsourcing, Teamwork

David A. ForsythGraphics, Projection Mapping

Wai-Tat FuHuman-Computer Interaction, Information Systems, Knowledge Representation

John Hart Data Visualization, Computer Graphics, Virtual Reality

Karrie Karahalios Social Computing, Human Computer Interaction, Social Visualization, Assistive Technologies, Fairness and Bias in Computing

Alex Kirlik Human-Computer Interaction, Human Factors, Cognitive Science and Engineering, Modeling and Supporting Human Judgment and Decision Making, Human-Automation Interaction

Ranjitha Kumar Data-Driven Design, Design Mining, User-Centered Machine Learning, UI/UX, Mobile/Web Applications, Social Networks, Fashion, Emoji

Steven M. Lavalle Virtual Reality, Human Perception

Klara NahrstedtQuality of Experience, Tele-Immersion, Multi-View Visualization, Embedded Sensors, Distributed and Parallel Systems

Hari Sundaram Voting, Improving Individual and Collective Decision Making, Information Asymmetry, MOOCs

☐ Intelligent Robotics Lab in the Coordinated Science Laboratory

☐ Intelligent Systems Research Theme in the Beckman Institute for Advanced Science and Technology

Interactive Computing is about effectively connecting computing services to human needs. The word Interactive is found in the names of our fields, like Human-Computer Interaction, and in the name of our topics, like Interactive Computer Graphics and Interactive Data Visualization.

Interaction is also at the core of engineering any technology relying on human engagement, which involves a process of designing, building, verifying, and maintaining, all with humans in the loop. Interactive Computing is also more than just humans interacting with technology, but also systems that enable people to interact with each other and the emergent benefits of social networking, crowd sourcing, and computer-supported cooperative work. And just as interactive computing relies on advances in other areas, such as databases, machine learning, networked systems and software engineering, the area of interactive computing impacts these other areas, especially when they rely on human engagement.

I N T E R A C T I V E C O M P U T I N G




Vikram Adve Programming Languages, Compilers, Parallel Programming, Domain-Specific Languages, Automated Debugging, Formal Verification, Software Repositories

Gul Agha Models for Concurrent Computation, Parallel and Distributed Algorithms

Mattox BeckmanParsers and Parser Generators, Clone Detection, Functional Programming and Type Classes, Matching Logic, Category Theory

Elsa Gunter Formal Methods, Programming Languages, Software Engineering, Semantics, Interactive Theorem Proving, Model Checking, Type Systems, Program Verification, Compiler Correctness

Darko Marinov Software Engineering, Software Testing

Jose Meseguer Formal Executable Specification and Verification, Software Architecture

Sasa Misailovic Program Optimization Systems, Approximate Computing Techniques

David Padua Program Analysis, Transformation, Optimization

Madhusudan Parthasarathy Formal Methods, Software Verification, Model Checking, Decidable Logics

Lawrence RauchwergerLanguages and Run-Time Systems for Parallel Computing, Compilers for Domain-Specific Parallel Languages

Grigore Rosu Software, Design, Semantics and Implementation of Programming Specification Languages

Mahesh Viswanathan Model Checking, Logic, Cyberphysical Systems, Software, Security

Tao Xie Software Engineering, Software Testing, Program Analysis, Software Analytics

Tianyin XuOperating Systems, Cloud and Datacenter Systems, System Reliability and Resilience, Large-Scale System Management, Configuration Management, Reliability Engineering

The growing complexity and scale of software poses formidable challenges for reliability, security, performance, and productivity. Our faculty tackle these problems by developing innovative techniques in programming language design and semantics; techniques and tools for formal verification, software testing, and automated debugging; and models and verification techniques for embedded systems that interact with physical entities.

☐ Coordinated Science Lab

☐ Assured Cloud Computing- University Center of Excellence in the Information Trust Institute

☐ Science of Security Lablet in the Information Trust Institute

☐ The LLVM Compiler Infrastructure

P R O G R A M M I N G L A N G U A G E S , F O R M A L M E T H O D S , A N D S O F T W A R E E N G I N E E R I N G


We are known for theoretical advances such as the Actor model of concurrency; rewriting logic and related semantic frameworks; concolic testing for automated test generation; automated logic reasoning; automated inference of specifications and invariants; and control-theoretic techniques for analyzing cyberphysical systems. We have also produced widely-used tools and techniques like the Maude rewriting engine; the LLVM compiler infrastructure; the Chisel optimization system for approximate computing; the first complete formalizations of C, Java, and JavaScript; regression test suite reduction techniques; and educational tools based on automated test generation (CodeHunt; Pex4Fun) that have attracted over a million users.



Nancy M. AmatoParallel Algorithms and Libraries, Parallel Graph Algorithms, Performance Modeling

Paul Fischer High-Order Numerical Methods for Partial Differential Equations, Scalable Parallel Algorithms, Iterative Solvers, Parallel Computing, Spectral Element Methods, Computational Fluid Dynamics

William Gropp High Performance Scientific Computing, Scalable Numerical Algorithms for PDEs, Numerical Software, Performance Analysis

Laxmikant Kale Simulation Software, Numerical Libraries, and Algorithms

Andreas Kloeckner Integral Equation Methods For PDEs, High-Order Finite Element Methods for Hyperbolic PDEs, Tools and Languages for High-Performance Computing, Time Integration

William Kramer Extreme-Scale Computing and Analytics, Performance Evaluation, Data and Storage Techniques

Luke Olson Numerical Analysis, Scientific Computing, Large-Scale Simulation, Multigrid and Iterative Methods, Finite Element Methods

Lawrence RauchwergerParallel Computing, Compilers, Parallel Libraries, High Performance Computing, Parallel Architecture, Exascale Computing

Marc Snir Large-Scale Parallel Systems, Algorithms, Libraries

Edgar Solomonik Numerical Linear Algebra, Tensor Computations, Parallel Algorithms, Quantum Chemistry, Quantum Simulation

☐ Blue Waters in the National Center for Supercomputing Applications

☐ Center for Exascale Simulation of Plasma-Coupled Combustion

☐ Computational Science and Engineering


☐ Parallel Computing Institute

☐ Theoretical and Computational Biophysics Group

Simulation plays a major role in nearly every area of science and engineering—from data analysis to physical models. Our faculty design, build, and analyze the behavior of numerical algorithms to ensure that numerical methods are accurate and that implementations are efficient.

We design and analyze the accuracy of methods, developing numerical approximations to partial differential equations with advanced finite element methods and integral equations. We also develop solvers for these problems, instrumenting techniques based on numerical linear algebra, iterative subspace methods, and multigrid methods. Our research explores the efficiency of these methods on a range of architectures and environments, from high-concurrency nodes, such as GPUs, to large-scale supercomputing systems. We explore parallel scalability and analyze performance in computing kernels from graph algorithms to sparse linear algebra.

S C I E N T I F I C C O M P U T I N G


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G R A D U A T E P R O G R A M S / 1 1

☐ Coordinated Science Laboratory

☐ Information Trust Institute

☐ Genomic Security and Privacy Theme in the Carl R. Woese Institute for Genomic Biology

☐ Security and Privacy Research at Illinois Group

At the same time society is increasingly relying on computers, a diverse array of adversaries are exploiting security vulnerabilities in these systems to compromise critical assets. There are also rising privacy concerns about how pervasive collection of data about individuals can be used to predict and manipulate their behavior. Illinois Security and Privacy faculty address security and privacy concerns with both theoretical and applied approaches.

They address security of computer and communication systems including: operating systems; auditing and data provenance; the Internet, wireless networks, and the “internet of things”; cloud computing; approximate computing; quality and resource management; and mobile computing. They also explore techniques related to security and privacy in a data science context such as: technologies for privacy-preserving data sharing based on cryptography, hardware, or generative models; distributed systems, crypto-currencies, and blockchains; adversarial machine learning; secure computation, zero-knowledge verifiable outsourcing, and related cryptography. These and other techniques are applied to a wide range of applications including: multi-sensory systems and multimedia; human factors and socio-technical considerations; power grids, autonomous vehicles and other cyber-physical systems; healthcare and genomics.

S E C U R I T Y A N D P R I V A C Y


Vikram Adve Secure Compilation, Program Analysis, Software Security, Debloating

Adam Bates Systems and Networks, Auditing, Internet of Things Security

Matthew CaesarNetwork Verification, Software Resilience, Model Checking

Roy A. CampbellCloud Computing, Big Data, Ubiquitous Computing, Microkernels

Chris Fletcher Hardware Security, Applied Cryptography

Brighten GodfreyNetwork Infrastructure Security and Verification

Carl GunterInternet of Things, Privacy, Data Science,Healthcare, Power Grid

Dakshita KhuranaSecure Computation, Cryptography, Privacy

Robin KravetzMobile Privacy, Wireless Security

Bo Li Machine Learning, Privacy Preserving Generative Models

Sasa MisailovicApproximate Computing across Full System Stack

Sibin MohanReal-Time and Cyber-Physical Systems, Internet-of-Things, Cloud Computing

Klara NahrstedtMobile, Multi-Sensory Systems, Quality and Resource Management, Energy Systems

Ling RenComputer Security, Applied Cryptography, Blockchain

Gang WangSecurity and Privacy, Internet Measurement, Human Factors

Tao XieMobile, Text Analytics, Testing, Program Analysist


Tarek Abdelzaher Sensors, Embedded and Real-Time Systems

Gul Agha Distributed Systems, Wireless Embedded Sensor Networks, Multi-Agent Systems

Adam Bates Security

Marco Caccamo Real-Time and Embedded Systems, Real-Time Scheduling and Security

Matthew Caesar Design, Analysis, and Verification of Wide-Area Networks and Distributed Systems

Roy H. Campbell Cloud Computing, Deep Learning Systems, Big Data, Security, Ubiquitous Computing, Micro kernels, Quantum Computing Systems, Health Data Analytics

Brighten Godfrey Cloud Networking, Network Verification, Machine Learning for Networks, Internet Architecture and Algorithms

Carl A. Gunter Security, Internet Architecture and Protocols, Smartphones and Internet of Things

Indranil Gupta Distributed Systems, Cloud Computing, Internet of Things Distributed Machine Learning, Industry Production Systems

Robin Kravets Networking, Wireless Networking, Mobile Computing, Internet of Things

Sasa Misailovic Approximate Computing Across Full System Stack

Sibin Mohan Real-Time and Embedded Systems, Cyber-Physical Systems, Internet of Things, Cloud Computing, Software-Defined Networks, Resiliency, Security

Klara Nahrstedt Quality of Experience, Tele-Immersion, Multi-View Visualization, Embedded Sensors, Distributed and Parallel Systems

Ling Ren Applied Cryptography, Computer Security and Distributed Algorithms

Lui ShaReal-Time Systems and Scheduling, Cyber-Physical Systems, Medical Systems Engineering

Deepak Vasisht Mobile Computing, Wireless Networking, Internet of Things, Ubiquitous Computing

Tianyin XuOperating Systems, Cloud and Datacenter Systems, System Reliability and Resilience, Large-Scale System Management, Configuration Management, Reliability Engineering

Working on problems that are directly relevant to industry, our faculty are advancing the state of the art in cloud computing and systems for big data, software defined networks, wired and datacenter networking, Internet of Things, wearable computing, mobile computing, multimedia systems, security, privacy, health-care engineering systems, and cyber-physical systems.

☐ Assured Cloud Computing-University Center of Excellence in the Information Trust Institute

☐ Coordinated Science Lab

☐ Information Trust Institute in the Coordinated Science Lab

S Y S T E M S A N D N E T W O R K I N G



We work collaboratively with industry partners including Google, Microsoft, AT&T, HP, and many others. Our research has also resulted in the creation of several startup companies. We produce creative and innovative students who become faculty at top-ranked schools, researchers at prestigious labs, and who join cutting-edge companies. Our courses are not just available to on-campus students, but a selection of them are also offered to off-campus students through Coursera MOOCs with enrollment numbers in the hundreds of thousands.



Nancy M. Amato Geometry, Parallel Algorithms, Computational Biology

Timothy Chan Computational Geometry, Algorithms, Data Structures

Chandra Chekuri Algorithms, Optimization

Mohammed El-Kebir Combinatorial Optimization, Integer Linear Programming, Computational Biology

Jeff Erickson Computational Geometry and Topology, Algorithms

Michael A. Forbes Pseudorandomness, Algebraic Computation, Computational Complexity

Brighten Godfrey Algorithms for and Analysis of Networks and Distributed Systems

Sariel Har-Peled Computational Geometry, Geometric Approximation Algorithms

Sheldon Jacobson Optimization, Operations Research

Dakshita Khurana Cryptography, Secure Computation, Zero-Knowledge, Differential Privacy

Ruta Mehta Algorithmic Game Theory, Mathematical Economics, Efficient Algorithms

Ling Ren Cryptography, Distributed Algorithms

Matus Telgarsky Machine Learning Theory

Mahesh ViswanathanModel Checking, Logic, Cyberphysical Systems, Software, Security

Tandy Warnow Graph Algorithms, Statistical Estimation, Heuristics for NP-Hard Optimization Problems, Experimental Algorithmics, Applications to Grand Challenges in Biology and Historical Linguistics

☐ Information Trust Institute in the Coordinated Science Lab


Theoretical computer science develops efficient algorithms and explores fundamental barriers to efficient and secure computation. Advances in algorithms can provide dramatic performance gains, which are critically important as the era of Moore's Law—and its promise of ever-increasing processor speeds—draws to a close.

T H E O R Y A N D A L G O R I T H M S


Our faculty develop algorithms to find optimal paths, trees, flows, clusters, and other important combinatorial structures in geometric and network data. For problems where computing the best possible solution is prohibitively expensive, we develop fast approximation algorithms to compute provably good solutions, and we explore the limits of what cannot even be approximated quickly. We develop algorithms that exploit geometric, algebraic, and topological properties of data that arise naturally in practice. Within cryptography, we develop protocols for secure multiparty computation and code obfuscation. In algorithmic game theory, we study the impact of strategic behavior among multiple agents. Our research, in addition to its fundamental importance, has many near-term applications in Computer Science and beyond.


The Research Park fosters opportunities for students and faculty to develop and commercialize new technology in conjunction with their academic work, enables established companies to collaborate with University of Illinois researchers, and gives students access to exciting internship opportunities. Research Park is also home to the EnterpriseWorks incubator facility and resource center for science and technology focused entrepreneurs.» http://researchpark.illinois.edu

The Technology Entrepreneur Center (TEC) provides students and faculty with the skills, resources, and experiences necessary to become successful innovators, entrepreneurs, and leaders who tackle grand challenges and change the world. TEC offers courses; venture and product competitions (such as the Cozad New Venture Competition and the Illinois Innovation Prize); plus workshops and other events that expose students to the concepts of technology innovation and market adoption.» http://tec.illinois.edu

CS researchers have access to Blue Waters, the fastest supercomputer at a university anywhere in the world. Capable of completing more than 1 quadrillion calculations per second on a sustained basis, its peak speed is more than 13 times faster and (almost 3 million times faster than the average laptop). Researchers use Blue Waters to predict the behavior of complex biological systems, understand how the cosmos evolved after the Big Bang, design new materials at the atomic level, predict the behavior of hurricanes and tornadoes, and simulate complex engineered systems like the power distribution system and airplanes and automobiles.» http://bluewaters.ncsa.illinois.edu

R E S E A R C H PA R KT E C H N O L O G Y E N T R E P R E N E U R C E N T E R

B L U E W A T E R S

Most CS faculty and students work in the Thomas M. Siebel Center for Computer Science, which has some of the best classrooms, research & instructional labs, and informal meeting spaces on the Illinois campus. Our collaborative culture brings the best minds together to work on some of society’s most complex problems—from medical information privacy, to climate modeling, to transforming raw data into useful information, to understanding the genome. Our students have boundless opportunities to conduct multidisciplinary research focused on the computing challenges that society faces now, and into the future.» http://cs.illinois.edu

T H O M A S M . S I E B E L C E N T E R

COLLABORATIVE SPACE WITH ACCESS TO SOME OF THE WORLD’S MOST POWERFUL COMPUTING RESOURCES

L I F E A S A I L L I N O I S C S S T U D E N T At Illinois, you have access to countless opportunities and support

to ensure an amazing experience both inside and outside the classroom.

D E PA R T M E N T O F C O M P U T E R S C I E N C E Visit the links below to learn more about life as a graduate student in our department.

CS Graduate Program Application Information: http://cs.illinois.edu/admissions/graduate

CS Graduate Program Policies: http://cs.illinois.edu/academics/graduate

Research: http://cs.illinois.edu/research

Faculty: http://cs.illinois.edu/people/faculty/department-faculty

CS Graduate Student Organization (CSGSO): https://www.facebook.com/csgso

G R A D U A T E C O L L E G E The Graduate College at the University of Illinois enrolls more than 10,000 graduate and professional students in more than 100 disciplines. Our graduate community is international in its composition and global in its impact.

Graduate College: http://grad.illinois.edu

Resources: http://grad.illinois.edu/students

Student Handbook and Policies: http://grad.illinois.edu/handbooks-policies

Diversity and Inclusion: http://grad.illinois.edu/diversity/about

New Student Quick Guide: http://grad.illinois.edu/quick-guide

G R A I N G E R C O L L E G E O F E N G I N E E R I N G Home to 12 academic departments, 9 multidisciplinary research centers, and 15 top-5 ranked degree programs, Grainger Engineering’s students, faculty, and alumni set the standard for excellence while solving the world’s greatest challenges.

Grainger Engineering: http://grainger.illinois.edu/academics/graduate

Engineering Update: http://grainger.illinois.edu/students/engineering-update

Meet Grainger Engineering Graduate Students (YouTube playlist): http://go.cs.illinois.edu/meetENGstudents

Engineering Career Services: http://ecs.engineering.illinois.edu

U N I V E R S I T Y O F I L L I N O I S Founded as the Illinois Industrial University in 1867, the University of Illinois at Urbana-Champaign was one of the original 37 public land-grant institutions created within 10 years of the signing of the Morrill Act by Abraham Lincoln in 1862.

Facts: http://illinois.edu/about/facts.html

Research: http://illinois.edu/research

Arts & Culture: http://illinois.edu/arts

News & Events: http://news.illinois.edu

International Student Resources: http://isss.illinois.edu

Off-Campus Housing: http://tenantunion.illinois.edu

On-Campus Housing: http://housing.illinois.edu

Student Health Insurance: http://www.uhcsr.com/illinois

Illinois Computer Science is committed to providing funding opportunities for graduate students. MS and PhD students may be offered a research or teaching assistantship—including a stipend, full tuition waiver, and partial fee waiver—making graduate school affordable.

Students may also qualify for fellowships offered by Illinois Computer Science, the College of Engineering, the Graduate College, or may apply to external funding agencies like the NSF. For more information on funding opportunities, please visit http://cs.illinois.edu/admissions/financial-aid.

F I N A N C I A L A I D O P P O R T U N I T I E S


E N G A G E I N S T U D E N T G R O U P SWhile on campus, there are over 1,000 students groups that provide a range of activities that can include leadership, mentorship, volunteering, professional development, and social interactions. To deepen your experience while in Siebel Center, get involved in a CS-affiliated student group:

Association for Computing Machinery (ACM), which organizes HackIllinois and the Reflections | Projections Conference: https://acm.illinois.edu https://hackillinois.org https://reflectionsprojections.org

Blacks & African Americans in Computing (BAAC): http://baac.engr.illinois.edu/

CS Graduate Student Organization (CSGSO):www.facebook.com/csgso

Founders, for entrepreneurs: www.founders.illinois.edu

Latinos in Computer Science (LCS): http://go.cs.illinois.edu/lcs

Society of Industrial and Applied Mathematics (SIAM): http://siam.cs.illinois.edu

Women in Computer Science (WCS): www.illinoiswcs.org

A N A F F O R D A B L E M I C R O - U R B A N E N V I R O N M E N TThe cost of living in Champaign-Urbana is 72.8% less than San Francisco, 59.4% cheaper tahn Seattle, 54.4% more economical than Boston, and 28.2% better than Atlanta [Sperling's Best Places, 2019]

Ranked the No. 4 small city for educated millenials. [Business Insider]

Learn about Champaign-Urbana’s micro-urban community:http://www.yourewelcomecu.comhttps://www.visitchampaigncounty.org

C A M P U S A C T I V I T I E S , A M E N I T I E S , A N D R E S O U R C E S

Activities and Recreation Center (ARC): www.campusrec.illinois.edu/facilities/arc

Illini Union: http://union.illinois.edu

Illinois Athletics: http://fightingillini.com

Krannert Art Museum: http://kam.illinois.edu

Krannert Center for the Performing Arts: www.krannertcenter.com

G E T A C Q U A I N T E D W I T H T H E C O M M U N I T Y

The Daily Illini, one of the country’s largest student-run newspapers: www.dailyillini.com

The News-Gazette, the newspaper and online source for news and advertising in East Central Illinois: www.news-gazette.com

40 North, a local nonprofit organization committed to cultivating creativity in Champaign County by promoting many community-wide events, programs, and resources: http://40north.org.

E X T R A O R D I N A R Y Q U A L I T Y O F L I F E


A L L T H E A M E N I T I E S O F B I G - C I T Y L I V I N G W I T H O U T T H E H A S S L E S

Conveniently centered between Chicago, Indianapolis, and St. Louis, the University of Illinois provides an entertainment and cultural hub on par with the country’s leading cities. Our campus community is home to Big 10 Division I sports; marquee theatrical, musical, dance performances; amazing festivals and fairs; and fantastic health and recreational facilities.

BLO

OMINGTON, IL50 MILES

ST. LOUIS, MO

170 MILES

CHICAGO, IL

140 MILES

SPRINGFIELD, IL87

MILES

MARKET PLACE MALL

INDI

ANAPOLIS, IN120 MILES

SIEBEL CENTER

CHAMPAIGN-URBANA, ILU

NIV

ER

SITY OF ILLINOIS CAMPU

SCO

LLEGE OF ENGIN

EERIN

G

GRAINGER LIBRARY

BARDEEN QUAD

DOWNTOWN URBANA

DOWNTOWN CHAMPAIGN

ILLINOIS TERMINAL

MEADOWBROOKPARK

WILLARDAIRPORT

POPULATION 100,000+

URBANA FARMER’S MARKET

MEMORIAL STADIUM

STATE FARM CENTER

ILLINI UNION AND MAIN QUAD

MCKINLEYHEALTH CENTER

KRANNERT CENTER FOR THE PERFORMING ARTS


ACTIVITIES & RECREATION CENTER (ARC)

University of Illinois at Urbana-ChampaignDepartment of Computer ScienceThomas M. Siebel Center for Computer Science201 N. Goodwin Avenue, Urbana, IL 61801-2302

W E D O T H E I M P O S S I B L E E V E R Y D A Y cs.illinois.edu

For more information visit go.cs.illinois.edu/GradPrograms or contact:Office of Graduate Programs(217) 333-4428On-Campus Programs: [email protected] Programs: [email protected]

C H O O S E Y O U R A D V A N C E D C S D E G R E E P R O G R A M☐ MS in Computer Science☐ PhD in Computer Science☐ Professional Master of Computer Science (MCS) ☐ On-Campus and Online ☐ MCS Data Science Track: Online Only☐ MS in Bioinformatics

A P P LY B Y T H E D E A D L I N E☐ MS/PhD in Computer Science: December 15 (Fall)☐ On-Campus MCS: January 15 (Fall)☐ Online MCS: October 15 (Spring), February 15 (Summer), & May 30 (Fall)☐ MCS Data Science Track: October 15 (Spring)

& May 30 (Fall)☐ MS in Bioinformatics: October 15 (Spring) & January 15 (Summer & Fall)

B E G I N Y O U R I L L I N O I S C O M P U T E R S C I E N C E A C A D E M I C C A R E E R T O D AY

http://cs.illinois.edu

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