Jingyi Liu (刘婧怡)
Jingyi Liu (刘婧怡)

PhD Student

Princeton University

About Me

I am a 4th year PhD student studying Theoretical Computer Science at Princeton University. I am fortunate to be co-advised by Professor Mark Braverman and Professor Matt Weinberg. I am broadly interested in algorithmic game theory and online learning. Recently, I am interested in how learning agents should behave in economic settings where decisions must respect long-run constraints and where the right notion of performance depends on structured benchmark classes that capture realistic behavior. I am also interested in multi-agent interactions and in what equilibrium notions are attainable.

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Interests
  • Algorithmic Game Theory
  • Online Learning and Equilibrium Computation
Education

  • PhD Student in Theoretical Computer Science

    Princeton University

  • BSc

    Harvey Mudd College

Publications
Mark Braverman, Jingyi Liu, Jieming Mao, Jon Schneider, Eric Xue (2025). A New Benchmark for Online Learning with Budget-Balancing Constraints. arXiv preprint arXiv:2503.14796.
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Toby Aldape, Jingyi Liu, Gregory Pylypovych, Adam Sheffer, Minh-Quan Vo (2024). Distinct distances in R3 between quadratic and orthogonal curves. European Journal of Combinatorics.
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Linda Cai, Jingyi Liu, S. Matthew Weinberg, Chenghan Zhou (2024). Profitable Manipulations of Cryptographic Self-Selection Are Statistically Detectable. 6th Conference on Advances in Financial Technologies (AFT 2024).
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Jingyi Liu, Isabel Duan, Santi Santichaivekin, Ran Libeskind-Hadas (2022). Distance Profiles of Optimal RNA Foldings. International Symposium on Bioinformatics Research and Applications.
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Santi Santichaivekin, Qing Yang, Jingyi Liu, Ross Mawhorter, Justin Jiang, Trenton Wesley, Yi-Chieh Wu, Ran Libeskind-Hadas (2021). eMPRess: a systematic cophylogeny reconciliation tool. Bioinformatics.
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