Publications
Check my Google Scholar profile for more information! (* stands for equal contribution.)
Economics and Computer Science
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Market Design for Generative AI: Beyond the Copyright Binary
, Maryam Farboodi, Negin Golrezaei, and Sepehr Shahshahani.Early versions accepted to / presented at...
- Wharton Accountable AI Research Conference (Feb, 2026)
- Stanford Market Design in the Age of AI Conference (Feb, 2026)
- Eleventh Marketplace Innovation Workshop (May, 2026)
- Intellectual Property Researchers Europe Conference (Jun, 2026)
- EC’26 Incentive-Based AI Alignment Workshop (Keynote) (Jul, 2026)
- Informs M&SOM Conference Service Operations SIG (Jul, 2026; 10 out of 96)
- Conference of Institutional & Organizational Economics (Jul, 2026)
- NBER Summer Institute Law and Economics Workshop (Jul, 2026)
- Informs Annual Meeting (Nov, 2026)
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Efficiency, Feasibility, and Incentive-Awareness in Constrained Online Resource Allocation
, Negin Golrezaei, and Patrick Jaillet.
Early version accepted to NeurIPS 2025 under the title “Incentive-Aware Dynamic Resource Allocation under Long-Term Cost Constraints.”
1st place in ACM Student Research Competition (SRC), SIGMETRICS 2025.Other presentations at...
- UMass Amherst Theory Seminar (Oct, 2025)
- Informs Annual Meeting (Oct, 2025)
- International Seminar on Foundational AI (Nov, 2025)
- TwoSigma PhD Fellowship Reception (Feb, 2026)
- Citadel Securities PhD Summit (Apr, 2026)
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Non-Monetary Mechanism Design without Priors: Achieving Efficiency via Adaptive Costly Audits
, Moïse Blanchard, and Patrick Jaillet.
Under review at Operations Research.
Early version accepted to COLT 2025 under the title “Non-Monetary Mechanism Design without Distributional Information: Using Scarce Audits Wisely.”
Bandits and Online Learning
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Policy Regret for Embedding Model Routing: Contextual Bandits with Low-Rank Experts
, Negin Golrezaei, and Patrick Jaillet. -
Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks
and Longbo Huang.
In Proceedings of the ACM on Measurement and Analysis of Computing Systems, 8(3):31, 2024.
Best Paper Award of ACM SIGMETRICS 2025. -
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen*, Jiatai Huang*, , and Longbo Huang. -
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning
Jiatai Huang*, , and Longbo Huang. -
Variance-Aware Sparse Linear Bandits
, Ruosong Wang, and Simon S. Du. -
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits
Jiatai Huang*, , and Longbo Huang.
Reinforcement Learning Theory
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Learning Adversarial Continuous MDPs with Bandit Feedback and Unknown Transitions
Aarush Kulkarni, Khang Nguyen, Ricardo Parada, Kenny Guo, William Chang, and . -
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation
, Qiwen Cui, and Simon S. Du. -
Refined Regret for Adversarial MDPs with Linear Function Approximation
, Haipeng Luo, Chen-Yu Wei, and Julian Zimmert. -
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback
, Haipeng Luo, and Liyu Chen.
Deep Learning Theory
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Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook, and . -
The Crucial Role of Normalization in Sharpness-Aware Minimization
, Kwangjun Ahn*, and Suvrit Sra.