Scholar
Seyed A Esmaeili
Google Scholar ID: kH0osN8AAAAJ
Postdoc, University of Chicago
Citations & Impact
Citations
294
H-index
9
i10-index
9
Publications
20
Co-authors
0
Contact
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Organizer and Program Chair: AAAI Workshop on Markets, Incentives, and Generative AI; Organizer and Presenter: AAAI Tutorial on Fair Clustering; Reviewer for various iterations of NeurIPS, ICML, ICLR, AAAI, AISTATS, FAccT, TMLR; Selected Publications: Data Auctions for Retrieval Augmented Generation, How to Strategize Human Content Creation in the Era of GenAI?, Robust Fair Clustering with Group Membership Uncertainty Sets, Welfare-Centric Clustering, Robust Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents, Replication-Proof Bandit Mechanism Design.
Research Experience
- Postdoctoral Researcher at the Data Science Institute at the University of Chicago, hosted by Haifeng Xu; previously a Postdoctoral Fellow at the Simons Laufer Mathematical Sciences Institute (SLMath) affiliated with the Algorithms, Fairness, and Equity program.
Education
- PhD in Computer Science from the University of Maryland, advised by John P. Dickerson and Aravind Srinivasan.
Background
- Research interests include machine learning, algorithmic fairness, and the strategic and game-theoretic aspects of machine learning. Specific work spans fair clustering, redistricting/gerrymandering, and strategic decision-making in multi-armed bandits. Recently, the focus has been on the intersection of LLMs, Generative AI, and game theory, including economic models of human–GenAI interactions and auctions and mechanism design for retrieval augmented generation (RAG).
Miscellany
- On the job market for 2025-2026.
Co-authors