Experience
December 2020 - present |
Senior Full-Stack EngineerAdobe, San Jose, CA |
July 2019 - December 2020 |
Research Scientist IIAdobe Research, San Jose, CA |
August 2016 - July 2019 |
Research Scientist IAdobe Research, San Jose, CA |
August 2013 - May 2016 |
Research AssistantUniversity of Maryland, College Park, MD |
June 2013 - August 2013 |
Software Engineer InternFoursquare, New York, NYImplement features to encourage user conversion and growth; ran A/B testing and reported on results. |
September 2011 - May 2013 |
Teaching AssistantDepartment of Computer Science, University of MarylandConduct discussion and review sessions; grade papers and projects; hold office hours. |
August 2008 - May 2010 |
Teaching AssistantDepartment of Computer Science, University of DelawareConduct lab and review sessions; grade papers and projects; hold office hours |
May 2008 - May 2010 |
Computer Lab AssistantDepartments of Computer Science and Computer & Electrical Engineering, University of DelawareMaintain department machines (Mac, Windows, Linux); set up, wire, and maintain networks; provide computer assistance for graduate students and professors. |
Education
September 2011 - May 2016 |
Ph.D in Computer ScienceUniversity of Maryland, College Park, MDThesis: A Visual Analytics Approach to Comparing Cohorts of Event Sequences |
September 2011 - May 2014 |
M.S. in Computer ScienceUniversity of Maryland, College Park, MDCourses: view
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September 2007 - May 2011 |
B.S. in Computer ScienceUniversity of Delaware, Newark, DEDegree with Distinction. Senior Thesis: "Parsing Java Method Names for Improved Software Analysis" Minor: Math Courses: view
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Projects
January 2014 - May 2016 |
CoCo: A Visual Analytics Approach to Comparing Cohorts of Event SequencesHuman-Computer Interaction Lab, University of Maryland, College ParkCo-advisors: Ben Shneiderman and Catherine Plaisant Designing, developing, and evaluating a visual analytics tool for performing comparison of two cohorts of event sequence data. More information: website |
August 2013 - May 2016 |
EventFlowHuman-Computer Interaction Lab, University of Maryland, College ParkCo-advisors: Ben Shneiderman and Catherine Plaisant Develop and maintain visual analytics tool for displaying and modifying event sequence data. More information: website |
May 2012 - January 2013 |
"Punctuation Input on Touchscreen Keyboards: Analyzing Frequency of Use and Mode-switching Costs"Human-Computer Interaction Lab, University of Maryland, College ParkAdvisor: Leah Findlater Updating and evaluating a 10-finger QWERTY touchscreen keyboard for the Microsoft Pixelsense. Running a user study with ten participants to evaluate performance of the keyboard against the status quo. More information: view AbstractNon-alphanumeric symbols are rarely considered in text input research even though some punctuation is more frequent than the least common English letters. In this paper, we first evaluate punctuation frequency in two contrasting sources (Twitter and Google N-Grams). We then present a controlled study to compare existing techniques for ten-finger punctuation input on touchscreens, particularly looking at the cost of switching to and from punctuation input mode: (1) a status quo keyboard, which provides an alternate keyboard layer with punctuation symbols, and (2) an approach where users draw punctuation symbols atop the Qwerty keyboard itself. Our findings underscore the importance of considering punctuation input in keyboard design and highlight the cost of mode- switching to enter punctuation marks.Links |
September - December 2012 |
TopicFlowDesigned and developed a novel visualization tool for analyzing tweets over time. Implemented live search, filtering, and brushing and linking interactions.More information: view Links
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January 2010 - May 2011 |
"Parsing Java Method Names for Improved Software Analysis"Software Analysis and Compilation Lab, University of DelawareCo-advisors: Lori L. Pollock, Vijay K. Shanker Developing, implementing, and evaluating a tool to automatically identify the parts-of-speech in multiword Java method names and chunk these words into meaningful phrases based on lexical relationships for improved software analysis. More information: view AbstractModern software engineering tools are driven by sophisticated automatic soft- ware analysis. Previous research indicates that the natural language (user-defined names) provides strong lexical clues about program behavior and structure and can be used to increase the effectiveness of various software engineering tools. Automatic analysis of the natural language usage in software requires accurate automatic parsing of the multi-word names (e.g., isPointInImage). This research focuses on developing the analysis techniques for an accurate parser for multi-word Java method names; this includes both a part-of-speech tagger and phrase chunker. These contributions form the foundation for natural language program analysis.Links |
June - August 2009 |
"Extending and Evaluating a Software Word Usage Model for C++"Software Analysis and Compilation Lab, University of DelawareGraduate Mentor: Emily Hill Examine differences of Java & C++ and apply a Software Word Usage Model (SWUM) to C++. More information: view AbstractCurrently, there are many automatic and semi-automatic tools to expedite software maintenance; however, most of these tools rely solely on the structural model of the program, while disregarding any semantic information from the natural language used by the programmer. In previous work towards solving this problem, we develepod a Software Word Usage Model (SWUM) for Java. SWUM enables software engineering tools to apply linguistic relations between words to form a more complete interpretation of the program. Although SWUM is currently defined for Java, we believe that SWUM is capable of representing programs in different programming languages. This project focuses on investigating the generality and extensibility of SWUM for programming languages beyond Java. The potential structural, semantic, and syntactic modications of SWUM for other languages were examined, particularly analyzing the differences between Java and C++. We evaluated the effectiveness of the phrases generated from SWUM for C++ code, and modified the SWUM construction algorithm to handle C++ features as needed.Links |
Publications
November 2021 |
“Just Follow the Lights”: A Ubiquitous Framework for Low-Cost, Mixed Fidelity Navigation in Indoor Built EnvironmentsPhilip Dasler, Sana Malik, Matthew Louis Maurielloin Proceedings of the IEEE VIS 2021 |
October 2021 |
An Evaluation-Focused Framework for Visualization Recommendation AlgorithmsZehua Zeng, Phoebe Moh, Fan Du, Jane Hoffswell, Tak Yeon Lee, Sana Malik, Eunyee Koh, Leilani Battlein Proceedings of the IEEE VIS 2021 Best Paper Honorable Mention |
August 2021 |
Learning to Recommend Visualizations from DataXin Qian, Ryan A Rossi, Fan Du, Sungchul Kim, Eunyee Koh, Sana Malik, Tak Yeon Lee, Joel Chanin Proceedings of the KDD '21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining |
April 2021 |
Generating Accurate Caption Units for Figure CaptioningXin Qian, Eunyee Koh, Fan Du, Sungchul Kim, Joel Chan, Ryan A Rossi, Sana Malik, Tak Yeon Leein Proceedings of the WWW '21: Proceedings of the Web Conference 2021 |
April 2020 |
Interactive Event Sequence Prediction for Marketing AnalystsFan Du, Shunan Guo, Sana Malik, Eunyee Koh, Sungchul Kim, Zhicheng Liuin Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (CHI 2020) |
April 2020 |
Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview StudyPo-Ming Law, Sana Malik, Fan Du, Moumita Sinhain Proceedings of the CHI 2020 Workshop on Detection and Design for Cognitive Biases in People and Computing Systems |
April 2020 |
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic BiasPo-Ming Law, Sana Malik, Fan Du, Moumita Sinhain Proceedings of Graphics Interface 2020 (GI 2020) |
April 2020 |
Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview StudyPo-Ming Law, Sana Malik, Fan Du, Moumita Sinhain Proceedings of the CHI 2020 Workshop on Detection and Design for Cognitive Biases in People and Computing Systems |
May 2019 |
DeepCompare: Visual and Interactive Comparison of Deep Learning ModelsSugeerth Murugesan, Sana Malik, Fan Du, Eunyee Koh, and Tuan Manh Laiin Proceedings of the IEEE computer graphics and applications (CG&A) 39 (5), 47-59 |
April 2019 |
Visualizing uncertainty and alternatives in event sequence predictionsShunan Guo, Fan Du, Sana Malik, Eunyee Koh, Sungchul Kim, Zhicheng Liu, Donghyun Kim, Hongyuan Zha, Nan Caoin Proceedings of the CHI 2019 |
October 2018 |
MAQUI: Interweaving Queries and Pattern Mining for Recursive Event Sequence ExplorationPo-Ming Law, Zhicheng Liu, Sana Malik, Rahul C Basolein IEEE Transactions on Visualization and Computer Graphics (TVCG). |
October 2018 |
Perceptual Similarity Ranking of Temporal Heatmaps Using Convolutional Neural NetworksSana Malik, Sungchul Kim, and Eunyee Kohin Proceedings of the 2018 Workshop on Understanding Subjective Attributes of Data, with the Focus on Evoked Emotions. South Korea, p. 25-31. |
April 2018 |
Interactive Campaign Planning for Marketing AnalystsFan Du, Sana Malik, Georgios Theocharous, and Eunyee Kohin Proceedings of the 2018 CHI Extended Abstracts on Human Factors in Computing Systems (CHI EA ’18). Montreal, CAN (2018). |
April 2018 |
Personalizable and Interactive Sequence Recommender SystemFan Du, Sana Malik, Georgios Theocharous, and Eunyee Kohin Proceedings of the 2018 CHI Extended Abstracts on Human Factors in Computing Systems (CHI EA ’18). Montreal, CAN (2018). |
February 2018 |
An Approach to Identify Delivery of Palliative Radiation Therapy Using Health Care Claims Data: A Proof-of-Concept Application of a Visual Analytics ToolEberechukwu Onukwugha, Jinani Jayasekera, James Gardner, Sana Malik, C Daniel Mullins, Arif Hussain, Jay P Ciezki, Chandana A Reddy, Brian Seal, Adriana Valderrama, and Young Kwokin Journal of Clinical Oncology: Clinical Cancer Informatics (JCO CCI). Vol. 2, p. 1-12. |
June 2017 |
Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic FocusFan Du, Ben Shneiderman, Catherine Plaisant, Sana Malik, and Adam Pererin IEEE Transactions on Visualization and Computer Graphics (TVCG). Vol. 3, Iss. 6. p. 1636-1649. |
May 2017 |
popHistory: Animated Visualization of Personal Web Browsing HistoryMatthew Carrasco, Eunyee Koh, and Sana Malikin Proceedings of the 2017 CHI Extended Abstracts on Human Factors in Computing Systems (CHI EA ’17). Denver, CO, USA (2016). p. 2429-2436. |
April 2017 |
WimNet: Vision Search for Web LogsSungchul Kim, Sana Malik, and Eunyee Kohin Proceedings of the 26th International Conference on World Wide Web Companion (WWW '17). Perth, AUS (2017). p. 803-804. |
May 2016 |
Simplifying Overviews of Temporal Event SequencesMatthew Louis Mauriello, Ben Shneiderman, Fan Du, Sana Malik, and Catherine Plaisantin Proceedings of the 2016 CHI Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16). San Jose, CA, USA (2016). p. 2217-2224. Best Paper Honorable Mention |
May 2016 |
High-Volume Hypothesis Testing for Large-Scale Web Log AnalysisSana Malik, Eunyee Kohin Proceedings of the 2016 CHI Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16). San Jose, CA, USA (2016). p. 1583-1590 |
May 2016 |
HIGH-VOLUME HYPOTHESIS TESTING: SYSTEMATIC EXPLORATION OF EVENT SEQUENCE COMPARISONSSana Malik, Ben Shneiderman, Fan Du, Catherine Plaisant and Margret Bjarnadottirin ACM Transactions on Interactive Intelligent Systems (TiiS), Volume 6 Issue 1, May 2016, Article No. 9 ACM New York, NY, USA |
March 2016 |
Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic FocusFan Du, Ben Shneiderman, Catherine Plaisant, Sana Malik, Adam Pererin IEEE Transactions on Vision and Computer Graphics, 2016 Mar 9. |
December 2015 |
UNDERSTANDING ADHERENCE AND PRESCRIPTION PATTERNS USING LARGE SCALE CLAIMS DATAMargret Bjarnadottir, Sana Malik, Eberechukwu Onukwugha, Tanisha Gooden, Cather- ine Plaisant in PharmacoEconomics 2016 Feb; 34(2):169-79. |
March 2015 |
Cohort Comparison of Event Sequences with Balanced Integration of Visual Analytics and StatisticsSana Malik, Fan Du, Megan Monroe, Eberechukwu Onukwugha, Catherine Plaisant and Ben Shneidermanin Proceedings of the 20th International Conference on Intelligent User Interfaces (IUI '15). p. 38-49. |
November 2014 |
An Evaluation of Visual Analytics Approaches to Comparing Cohorts of Event SequencesSana Malik, Fan Du, Megan Monroe, Eberechukwu Onukwugha, Catherine Plaisant and Ben Shneidermanin IEEE VIS Workshop on Visualizing Electronic Health Record Data |
August 2014 |
Visual Analysis of Topical Evolution in Unstructured Text: Design and Evaluation of TopicFlowAlison Smith, Sana Malik, and Ben ShneidermanLecture Notes on Social Network Analysis, Springer (to appear) |
August 2013 |
TopicFlow: Visualizing Topic Alignment of Twitter Data over TimeSana Malik, Alison Smith, Timothy Hawes, Panagis Papadatos, Jianyu Li, Cody Dunne, Ben Shneidermanin Proceedings of 2013 IEEE/ACM ASONAM, ACM |
May 2013 |
Part-of-Speech Tagging of Program Identifiers for Improved Text-based Software Engineering ToolsSamir Gupta, Sana Malik, Lori Pollock and K. Vijay-Shankerin Proceedings of the 21st International Conference on Program Comprehension (ICPC). Best paper award. |
Patents
August 2021 |
"GENERATING DIGITAL EVENT SEQUENCES UTILIZING A DYNAMIC USER PREFERENCE INTERFACE TO MODIFY RECOMMENDATION MODEL REWARD FUNCTIONS"US Patent No. 11,085,777 |