Rafael Veras +1 437-345-4079

rafa.veras@outlook.com

github.com/rafaveguim

linkedin.com/in/rafaveras

Google Scholar

EDUCATIONUniversity of OntarioInstitute of TechnologyFaculty of SciencePhD in Computer ScienceExpected Grad. Jan 2019M.Sc in Computer ScienceGrad. Aug 2013

Universidade Federal do ParáBS Computer ScienceGrad. May 2011

SKILLSLanguages:R, Python, JavaScript, C++, Java, SQL

Libraries:D3.js, scikit-learn, Pandas, Numpy,ggplot2, Keras, Spacy

Methods:Hypothesis testing, user studies,crowdsourcing, parallel computing,GLMMs, language models, statisticalanalysis, information theory.

HOBBIESCooking with my spouseBrazilian Jiu-JitsuPlaying FIFA with friends

12.14.2018

EXPERIENCEMicrosoft Research Jul – Oct 2017Research Intern Redmond, WA

• Collaboration between natural language processing andvisualization teams• Built a visual analytics tool to help control the quality of sentencesspoken by an AI-powered chatbot.

University of Ontario Institute of Technology 2011 – 2018Teaching Assistant Oshawa, ON

Delivered lectures and tutorials, created coursework material, held officehours, and graded assignments and exams. Courses:• Information Visualization• Human-Computer Interaction• Programming Workshop• Introduction to Programming

Rede de Informatica Jun 2010 – Jul 2011Java Developer Belém, Brazil

• Designed and developed new visualization components for thePRISMA visualization suite.• Wrote successful grants for research projects.

PUBLICATIONS[1] Veras, Rafael and Christopher Collins. “Saliency Deficit and Motion Outlier

Detection in Animated Scatterplots”. In: Proc. of the 2019 CHI Conference onHuman Factors in Computing Systems. ACM. 2019, To appear.

[2] Veras, Rafael and Christopher Collins. “Optimizing Hierarchical Visualizationswith the Minimum Description Length Principle”. In: IEEE Transactions onVisualization and Computer Graphics 23.1 (2017), pp. 631–640.

[3] Veras, Rafael, Christopher Collins and Julie Thorpe. “On Semantic Patterns ofPasswords and their Security Impact.” In: Proc. of the Network andDistributed System Security Symposium. 2014.

[4] Veras, Rafael, Julie Thorpe and Christopher Collins. “Visualizing semantics inpasswords: The role of dates”. In: Proc. of Int. Symposium on Visualization forCyber Security. ACM. 2012, pp. 88–95.

[5] Veras, Rafael, Erik Paluka, Meng-Wei Chang, Vivian Tsang, Fraser Shein andChristopher Collins. “Interaction for Reading Comprehension on Mobiledevices”. In: Proc. of the Int. Conf. on Human-computer Interaction withMobile Devices & Services. ACM. 2014, pp. 157–161.

[6] Santiago Bonada, Veras, Rafael and Christopher Collins. “Personalized Viewsfor Immersive Analytics”. In: Proc. of the ACM ISS Workshop on ImmersiveAnalytics. ACM. 2016, pp. 83–89.

PROUD OF• First person in my family to attend grad school.• Learned spoken English while hosting travelers throughcouchsurfing.com.• Organized public events to discuss improvements in myneighborhood in Brazil, as well as skills workshops, and collectedthousands of signatures to pass an anti-corruption bill.

Proj

ects

NLP/Security

Information Visualization

Visualization + AI

Created the first computational modelof human-chosen passwords that capturessemantic and syntactic patterns. Studied the details of training such models with publicly available password leaks and evaluated their implications to password security. Results showed that language patterns in password creation dramatically reduce the security of passwords.

Ongoing project in collaboration with Microsoft Research aims at supporting visual analysis of sentences spoken by an artificial conversational agent. A key constraint is presenting agent sentences in the context of the training data.

Veras, Rafael, Christopher Collins, and Julie Thorpe. "On semantic patterns of passwords and their security impact." NDSS. 2014. 91 citations. (AR: 55/293 = 18.7%)

Veras, Rafael, and Christopher Collins. "Optimizing hierarchical visualizations with the minimum description length principle." IEEE Transactions on Visualization and Computer Graphics. 2017.8 citations. (AR: 38/165 = 23%)

Veras, Rafael, and Christopher Collins. "Saliency Deficit and Motion Outlier Detection in Animated Scatterplots." ACM CHI 2019 Forthcoming. (AR: 705/2960 = 23.8%)

Veras, Rafael, Julie Thorpe, and Christopher Collins. "Visualizing semantics in passwords: the role of dates" VizSec. 2012. 41 citations.

Hierarchical Visualization Optimization. Created an algorithm for automated summarization of large hierarchies for visualization purposes. The optimized visualizations achieve a good balance between level of detail and clutter, and automatically adjust the information depending on screen size. As a result, large hierarchical data can be viewed in mobile displays.

Discriminability Tests. A semi-automated approach for evaluating the quality of visualization designs. The tests leverage perception-based image similarity measures to score the discriminability of competing information visualization designs (e.g., in A/B scenarios). The automated nature of the tests helps with cutting the costs of validation, traditionally done with user studies. The approach is validated against published empirical studies on the effectiveness of visualization encodings. (This project is in progress.)

Saliency Deficit. Evaluated the effectiveness of an important analytical task (outlier detection) in multivariate animated scatterplots through a crowdsourced controlled experiment. Results showed that despite motion being a strong visual cue, users mostly fail to identify motion outliers due to interference of other visual channels (color, size, position, etc.). I proposed an empirical model for predicting the probability of correct outlier detection.