William Brown



I recently completed a PhD in Computer Science at Columbia, where I was incredibly fortunate to be advised by Christos Papadimitriou and Tim Roughgarden in the Theory group. My research interests lie at the intersection of machine learning and game theory, with a focus on learning in the presence of strategic, adversarial, or otherwise dynamic behavior. Previously, I graduated from Penn in 2019 with an MS in Data Science and a BS in Computer Science and Philosophy.


  • Online Recommendations for Agents with Discounted Adaptive Preferences
    Arpit Agarwal, William Brown
    ALT 2024. [arXiv]
  • Is Learning in Games Good for the Learners?
    William Brown, Jon Schneider, Kiran Vodrahalli
    NeurIPS 2023 (Spotlight). [arXiv] [talk]
  • Diversified Recommendations for Agents with Adaptive Preferences
    Arpit Agarwal, William Brown
    NeurIPS 2022. [arXiv] [talk]
  • Private Synthetic Data for Multitask Learning and Marginal Queries
    Giuseppe Vietri, Cedric Archambeau, Sergul Aydore, William Brown, Michael Kearns, Aaron Roth, Ankit Siva, Shuai Tang, Steven Wu
    NeurIPS 2022. [arXiv]
  • Learning in Multi-Player Stochastic Games
    William Brown
    UAI 2021. [arXiv]
  • Differentially Private Query Release Through Adaptive Projection
    Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit Siva
    ICML 2021 (Long presentation). [arXiv] [talk]
  • Targeted Intervention in Random Graphs
    William Brown, Utkarsh Patange
    SAGT 2020. [arXiv]
  • Change Point Detection in Software Performance Testing
    David Daly, William Brown, Henrik Ingo, Jim O'Leary, David Bradford
    ICPE 2020. [arXiv] [blog]


  • Online Stackelberg Optimization via Nonlinear Control
    William Brown, Christos Papadimitriou, Tim Roughgarden
    In submission.
  • Online Portfolio Selection with Adversarial Transaction Costs
    William Brown, Yikai Zhang
    In submission.


  • Machine Learning Research - Morgan Stanley (2023 - )
  • Applied Science - Amazon Web Services (2020 - 2022)
  • Applied Research - Two Sigma Labs (Summer 2019)
  • Data Engineering - Two Sigma (Summer 2018)
  • Software Engineering - MongoDB (Summer 2017)
  • Data Science - American Family Insurance (Summer 2016)


  • Teaching Assistant - COMS 6998-001: Foundations of Blockchains (Fall 2020)