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Research

Journal Articles

  1. "Efficient Decentralized Multi-agent Learning in Asymmetric Bipartite Queueing Systems."
    with Daniel Freund and Wentao Weng.
    Operations Research. Vol. 72, No. 3 (2024): 1049-1070.
    Conference version: 35th Annual Conference on Learning Theory (COLT 2022).
    Journal version
    Video of a 60-minute talk that Daniel gave in the SNAPP seminar series in April 2023.
    Finalist in the Applied Probability Society Student Paper Competition (2022).
  2. "Learning in Stackelberg Games with Non-myopic Agents"
    with Nika Haghtalab,, Sloan Nietert, and Alexander Wei.
    Operations Research. Forthcoming (2025).
    Conference version: 23rd ACM Conference on Economics and Computation (EC 2022).
  3. “Static Pricing for Multi-unit Prophet Inequalities.”
    with Shuchi Chawla and Nikhil Devanur.
    Operations Research. Vol. 72, No. 4 (2024): 1388-1399.
    Conference version: 17th Conference on Web and Internet Economics (WINE 2021).
    Journal version.
  4. "Corruption-robust Exploration in Episodic Reinforcement Learning."
    with Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
    Mathematics of Operations Research. Vol. 50, No. 2 (2024): 1277-1304.
    Conference version: 34th Annual Conference on Learnint Theory (COLT 2021).
    Journal version.
    Video of a 60-minute talk that I gave in the RL Theory seminar series in November 2020.
  5. "Contextual Search in the Presence of Adversarial Corruptions."
    with Akshay Krishnamurthy, Chara Podimata, and Robert Schapire.
    Operations Research. Vol. 71, No. 4 (2023): 1120-1135.
    Conference version: 53rd ACM Symposium on Theory of Computing (STOC 2021).
    Journal version.
    Video of a 45-minute talk that Chara gave at the Simons Institute in September 2022.
  6. "Competitive Caching with Machine Learned Advice."
    with Sergei Vassilvitskii.
    Journal of the ACM. Vol. 68, No. 4, Art. 24 (2021): 1-25.
    Conference version: 35th International Conference on Machine Learning (ICML 2018).
    Journal version.
  7. "Small-loss Bounds for Online Learning with Partial Information."
    with Karthik Sridharan and Éva Tardos.
    Mathematics of Operations Research. Vol. 47, No. 3 (2022): 2186-2218.
    Conference version: 31st Annual Conference on Learning Theory (2018).
    Journal version.
    Video of a 10-minute talk that I gave at the COLT 2018 conference in July 2018.
    Finalist in the INFORMS Nicholson Student Paper Competition (2018).
  8. "Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework."
    with Siddhartha Banerjee and Daniel Freund.
    Operations Research. Vol. 70, No. 3 (2022): 1783-1805.
    Conference version: 18th ACM Conference on Economics and Computation (EC 2017).
    Journal version.
    Video of a 20-minute talk that I gave at the EC 2017 conference in June 2017.
    Finalist in the Applied Probability Society Student Paper Competition (2017).

Working Papers

  1. "Scheduling with Uncertain Holding Costs and its Application to Content Moderation."
    with Caner Gocmen, Deeksha Sinha, and Wentao Weng.
    Major Revision at Management Science.
  2. "Learning to Defer in Congested Systems: The AI-Human Interplay."
    with Wentao Weng.
    Under second-round review at Operations Research (after Major Revision).
    Video of a 60-minute talk that I gave in the SNAPP seminar series in May 2024.
    Finalist in the Junior Faculty Interest Group Paper Competition (2024).
  3. "Social Learning with Limited Attention: Negative Reviews Persist under Newest First."
    with Jackie Baek and Atanas Dinev.
    Under second-round review at Operations Research (after Major Revision).
    Conference version: 25th ACM Conference on Economics and Computation (EC 2024).
    Accepted for presentation in the 2025 MSOM SIG (Service Science).
    Finalist in the Junior Faculty Interest Group Paper Competition (2025).
  4. "The Transient Cost of Learning in Queueing Systems."
    with Daniel Freund and Wentao Weng.
    Under second-round review at Operations Research (after Reject-and-Resubmit).
    Conference version: 37th Conference on Neural Information Processing Systems (NeurIPS 2023).
  5. "Group Fairness in Dynamic Refugee Assignment."
    with Daniel Freund, Elisabeth Paulson, Bradley Sturt, and Wentao Weng.
    Major Revision at Operations Research.
    Conference version: 24th ACM Conference on Economics and Computation (EC 2023).
    Video of a 60-minute talk that Daniel gave at the TOC4Fairness in February 2024.
    Video of a 18-minute talk that Wentao gave at the EC 2023 conference in June 2023.
  6. “Stochastic Bandits Robust to Adversarial Corruptions.”
    with Vahab Mirrokni and Renato Paes Leme.
    Conference version: 50th ACM Symposium on Theory of Computing (STOC 2018).
    Video of a 75-minute bootcamp talk that I gave at the Simons Institute in August 2022.
    Video of a 20-minute talk that I gave at the STOC 2018 conference in June 2018.
  7. “Learning and Efficiency in Games with Dynamic Population.”
    with Vasilis Syrgkanis, and Éva Tardos.
    Major Revision at Mathematics of Operations Research.
    Conference version: 27th ACM-SIAM Symposium on Discrete Algorithms (SODA 2016).
    Video of a 45-minute talk that Éva gave at the Simons Institute in March 2018.

Conference Publications Not Listed Above

  1. "Bayesian Decision-Making under Misspecified Priors with Applications to Meta-Learning."
    Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert Schapire (contributional author order).
    35th Annual Conference on Neural Information Processing Systems (NeurIPS 2021).
  2. "Constrained Episodic Reinforcement Learning in Concave-convex and Knapsack Settings."
    with Kianté Brantley, Miroslav Dudík, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
    34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020).
  3. "Bandits with Adversarial Scaling."
    with Vahab Mirrokni and Renato Paes Leme.
    37th International Conference on Machine Learning (ICML 2020).
    Video of a 15-minute talk that I gave at the ICML 2020 conference in July 2020.
  4. "Feedback Graph Regret Bounds for Thompson Sampling and UCB."
    with Éva Tardos and Drishti Wali.
    31st International Conference on Algorithmic Learning Theory (ALT 2020).
  5. "Advancing Subgroup Fairness via Sleeping Experts."
    with Avrim Blum.
    11th Innovations in Theoretical Computer Science Conference (ITCS 2020).
  6. "On Preserving Non-discrimination when Combining Expert Advice."
    with Avrim Blum, Suriya Gunasekar, and Nathan Srebro.
    32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018).
  7. "Learning in Games: Robustness of Fast Convergence."
    with Dylan Foster, Zhiyuan Li, Karthik Sridharan, and Éva Tardos.
    30th Annual Conference on Neural Information Processing Systems (NeurIPS 2016).
    Video of a 30-minute talk that I gave at the YoungEC 2017 workshop in January 2017.
  8. "Influence Maximization in Switching-selection Threshold Models."
    with Dimitris Fotakis, Evangelos Markakis, and Svetlana Obraztsova.
    7th International Symposium on Algorithmic Game Theory (SAGT 2014).

PhD Dissertation