Kazi Shahrukh Omar
Research Assistant at Electronic Visualization Laboratory (EVL) advised by Dr. Fabio Miranda. Visit my profile at EVL's website here.
CS PhD student @ University of Illinois Chicago.
My research leverages skills in visualization & visual analytics, big data analysis, and applied machine learning. Specifically, I focus on utilizing these skills within urban planning and health informatics, 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. I also love watching series and movies, as well as traveling, although I've had fewer opportunities to travel lately. Recently, I've developed a growing interest in board games.
News
Oct 2024 | Attended CLEETS Fall School on decarbonizing road transportation with global experts (Certificate). š± |
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Aug 2024 | Open sourced VIGMA, a framework for handling the workflow of gait data processing, analysis, and visualization. |
Aug 2024 | Began role as a Research Assistant with the CLEETS team, contributing to decision support tools for cross domain urban planning. ā»ļø |
May 2024 | Joined as a full-time Research Assistant for Summer 2024 at the CogMoBal Lab of Applied Health Sciences Dept, UIC, working on developing an open-access visual analytics system for gait data processing, analysis, and visualization. |
Feb 2024 | āDeep Umbra: A Generative Approach for Sunlight Access Computation in Urban Spacesā has been accepted for publication in the journal āIEEE Transactions on Big Dataā. View the paper here. |
Selected publications
- 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