Kazi Shahrukh Omar

CS PhD student @ University of Illinois Chicago.
Research Assistant at Electronic Visualization Laboratory (EVL) advised by Dr. Fabio Miranda.
My research leverages skills in visualization & visual analytics, big data analysis, and applied machine learning. Specifically, I focus on utilizing these skills within diverse domains like urban planning and healthcare, aiming to enhance the ability of domain experts to efficiently analyze large-scale data and uncover complex patterns through advanced visual analytics systems. My work also involves open-sourcing projects to foster further research in these areas, that include: (1) VIGMA, a comprehensive system for gait data processing, analysis, and visualization, and (2) Deep Umbra, an accumulated shadow computation technique along with visual analytics system and shadow dataset for over 100 cities.
Outside of my academic work, I enjoy playing guitar, listening to music, and a little bit of reading. Recently, I've developed a growing interest in board games and anime.
News
Jun 2025 | Presented poster at the Sustainability Research + Innovavtion Congress 2025. |
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May 2025 | Started full-time role as“PhD Data Visualization Intern” at Epsilon working with the Decision Sciences Visual Analytics team. 💼 |
Apr 2025 | “VIGMA: An Open-Access Framework for Visual Gait and Motion Analytics” has been accepted for publication in the journal “IEEE Transactions on Visualization and Computer Graphics”. View the paper here. |
Mar 2025 | Abstract titled “Developing an Open Computational Framework for Decision Support Across Transportation, Weather, and Public Health” accepted for presentation at the Sustainability Research + Innovavtion Congress 2025. View the poster here |
Oct 2024 | Attended CLEETS Fall School on decarbonizing road transportation with global experts (Certificate). 🌱 |
Selected publications
- VIGMA: An Open-Access Framework for Visual Gait and Motion AnalyticsIEEE Transactions on Visualization and Computer Graphics, 2025
- Deep Umbra: A Generative Approach for Sunlight Access Computation in Urban SpacesIEEE Transactions on Big Data, 2024
- Crowdsourcing and Sidewalk Data: A Preliminary Study on the Trustworthiness of OpenStreetMap Data in the USASSETS UrbanAccess Workshop, 2022