Taylor Lundy

Taylor Lundy

PhD Candidate, Computer Science · University of British Columbia

I work at the intersection of algorithmic game theory, mechanism design, and AI for economics.

My research studies strategic behavior in mobile games, NFT markets, and the economic reasoning capabilities of large language models.

I am advised by Kevin Leyton-Brown.

Algorithmic Game Theory Mechanism Design Digital Goods & NFTs LLM Evaluation Economic Rationality
Email: tlundy@cs.ubc.ca
Web: cs.ubc.ca/~tlundy
Photo of Taylor Lundy
Department of Computer Science
University of British Columbia · Vancouver, Canada

Publications Computer Science

  • 2025
    Reasoning Models are Test Exploiters: Rethinking Multiple-Choice.
    Narun K. Raman, Taylor Lundy, and Kevin Leyton-Brown.
    Working paper; arXiv preprint, 2025.
    [arXiv]
  • 2025
    Multidimensional Bayesian Utility Maximization: Tight Approximations to Welfare.
    Kira Goldner and Taylor Lundy.
    Advances in Neural Information Processing Systems (NeurIPS), 2025.
    [arXiv]
  • 2025
    STEER-ME: Assessing the Microeconomic Reasoning of Large Language Models.
    Narun K. Raman, Taylor Lundy, Thiago Amin, Jesse Perla, and Kevin Leyton-Brown.
    NeurIPS 2025, Datasets and Benchmarks Track.
    [arXiv] [OpenReview]
  • 2025
    NFTs as a Data-Rich Test Bed: Conspicuous Consumption and its Determinants.
    Taylor Lundy, Narun Raman, Scott Duke Kominers, and Kevin Leyton-Brown.
    The Web Conference (WWW), 2025.
    [arXiv] [WWW]
  • 2024
    STEER: Assessing the Economic Rationality of Large Language Models.
    Narun K. Raman, Taylor Lundy, Samuel Amouyal, Yoav Levine, Kevin Leyton-Brown, and Moshe Tennenholtz.
    International Conference on Machine Learning (ICML), 2024.
    [arXiv]
  • 2024
    UNSAT Solver Synthesis via Monte Carlo Forest Search.
    Chris Cameron, Jason Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, and Kevin Leyton-Brown.
    International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR), 2024.
    [arXiv]
  • 2024
    Pay to (Not) Play: Monetizing Impatience in Mobile Games.
    Taylor Lundy, Narun Raman, Hu Fu, and Kevin Leyton-Brown.
    AAAI Conference on Artificial Intelligence (AAAI), 2024.
    [arXiv] [AAAI]
  • 2022
    The Perils of Learning Before Optimizing.
    Chris Cameron, Jason Hartford, Taylor Lundy, and Kevin Leyton-Brown.
    AAAI Conference on Artificial Intelligence (AAAI), 2022.
    [AAAI]
  • 2020
    Limitations of Incentive Compatibility on Discrete Type Spaces.
    Taylor Lundy and Hu Fu.
    AAAI Conference on Artificial Intelligence (AAAI), 2020.
    [AAAI]
  • 2020
    Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver.
    Devon Graham, Satish Kumar Sarraf, Taylor Lundy, Ali MohammadMehr, Sara Uppal, Tae Yoon Lee, Hedayat Zarkoob, Scott Duke Kominers, and Kevin Leyton-Brown.
    arXiv preprint, 2020.
    [arXiv]
  • 2019
    Allocation for Social Good: Auditing Mechanisms for Utility Maximization.
    Taylor Lundy, Alexander Wei, Hu Fu, Scott Duke Kominers, and Kevin Leyton-Brown.
    ACM Conference on Economics and Computation (EC), 2019.
    [EC] [PDF]