Scholar
Yan DAI (戴言)
Google Scholar ID: gkG4z3IAAAAJ
PhD Student, ORC, MIT
Citations & Impact
Citations
174
H-index
7
i10-index
7
Publications
12
Co-authors
12
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Publications: 'Incentive-Aware Dynamic Resource Allocation under Constraints' accepted to NeurIPS 2025; 'Adversarial Network Optimization under Bandit Feedback' won Best Paper Award at ACM SIGMETRICS 2025 and 1st Place in ACM Student Research Competition (SRC), SIGMETRICS 2025; 'Non-Monetary Mechanism Design without Distributions' accepted to COLT 2025; 'Refined Best-of-Both-Worlds Heavy-Tailed MABs' accepted to ICLR 2025 as a Spotlight Paper (5.1%); 'Adversarial Network Optimization under Bandit Feedback' published in the ACM journal POMACS; 'Refined Linear Markov Games' accepted to COLT 2024; 'Adam is FTRL in Disguise' accepted to ICML 2024; 'Role of Normalization in SAM' accepted to NeurIPS 2023; 'Refined Adversarial Linear(-Q) MDPs' and 'Banker-OMD Framework for Delayed Bandits' accepted to ICML 2023; 'Variance-Aware Sparse Linear Bandits' accepted to ICLR 2023; 'FTPL in Adversarial MDPs' accepted to NeurIPS 2022; 'Best-of-Both-Worlds Heavy-Tailed MABs' accepted to ICML 2022.
Research Experience
- Currently conducting research at the Operations Research Center, MIT, focusing on the intersection of Economics and Computer Science.
Education
- Earned a Bachelor’s degree from Yao Class, Tsinghua in June 2024, under the guidance of Prof. Longbo Huang, Prof. Haipeng Luo, Prof. Simon S. Du, and Prof. Suvrit Sra.
Background
- A second-year PhD student at the Operations Research Center (ORC), MIT, co-advised by Prof. Patrick Jaillet and Prof. Negin Golrezaei. Research focuses on the intersection of Economics and Computer Science (EconCS), specifically resolving strategic behaviors in economic systems via online learning tools. Broadly interested in learning theory topics such as bandits, online learning, reinforcement learning theory, and deep learning theory.
Miscellany
- Served as a reviewer for multiple journals and conferences, including JMLR, TPAMI, Performance Evaluation, COLT 2025, ICML 2025/2023, NeurIPS 2025/2024/2023/2022, ICLR 2025/2024, AISTATS 2025/2023/2022, AAAI 2026, ALT 2023.
