CV

Education

• Ph.D. in Computer Science, University of Chicago, 2026 (expected)
• M.S. in Computer Science, University of Chicago, 2023 (expected)
• B.A. in Computer Science, University of Minnesota - Twin Cities, 2021

Work experience

• Fall 2021 - Present: Graduate Research Assistant
  • University of Chicago
  • Research projects spanning data systems, machine learning, and sustainability
• Fall 2021 - Present: Graduate Teaching Assistant
  • University of Chicago
  • Undergraduate data science and engineering courses
• Summer 2022: Data Science R&D Intern
  • BigID
  • Structured data profiling
• Summer 2020: Software Engineer Intern
  • US Bank
  • Data dictionary automation and features for a large payment processing application
• Spring 2020: Technical Writing Intern
  • Kite
  • Wrote code and (speaking) scripts for entertaining educational videos on machine learning
  • Developed documentation for common Python questions
• 2019-2021: Undergraduate Research Assistant
  • University of Minnesota - Twin Cities
  • Research in computational social science, machine learning, and computational statistics

Publications

A comparison of machine learning algorithms applied to american legislature polarization

Gabriel Mersy, Vincent Santore, Isaac Rand, Corrine Kleinman, Grant Wilson, Jason Bonsall, and Tyler Edwards. 2020. A Comparison of Machine Learning Algorithms Applied to American Legislature Polarization. In Proceedings of the 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), August 11 - Aug 13, 2020, virtual, 451-456. https://doi.org/10.1109/IRI49571.2020.00075

Source Separation and Depthwise Separable Convolutions for Computer Audition (Student Abstract)

Gabriel Mersy and Jin Hong Kuan. 2021. Source Separation and Depthwise Separable Convolutions for Computer Audition (Student Abstract). In Proceedings of the AAAI Conference on Artificial Intelligence, 35, 18 (May 2021), 15847-15848.

Using machine learning to model trace behavioral data from a game-based assessment

Auer, E. M., Mersy, G., Marin, S., Blaik, J., & Landers, R. N. (2022). Using machine learning to model trace behavioral data from a game-based assessment. International Journal of Selection and Assessment, 30, 82–102.

You are what you click: using machine learning to model trace data for psychometric measurement

Richard N. Landers, Elena M. Auer, Gabriel Mersy, Sebastian Marin & Jason Blaik (2022) You are what you click: using machine learning to model trace data for psychometric measurement, International Journal of Testing, 22:3-4, 243-263, DOI: 10.1080/15305058.2022.2134394

Hierarchical Residual Encoding for Multiresolution Time Series Compression

Bruno Barbarioli, Gabriel Mersy, Stavros Sintos, and Sanjay Krishnan. 2023. Hierarchical Residual Encoding for Multiresolution Time Series Compression. 2023 International Conference on Management of Data (SIGMOD 2023).

Toward a Life Cycle Assessment for the Carbon Footprint of Data

Gabriel Mersy, and Sanjay Krishnan. 2023. Toward a Life Cycle Assessment for the Carbon Footprint of Data. 2nd Workshop on Sustainable Computer Systems (HotCarbon 2023).