Jiale Han
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PhD Candidate |
About me
Hi, I am a fourth-year Ph.D. candidate in the Department of Statistics and Data Science at UCLA. I received my B.S. in Mathematics from University of Chinese Academy of Sciences in 2022. In Summer 2025, I worked as a Machine Learning Research Intern with the Advertising Mechanism Team at JD.com (Beijing), conducting research on auto-bidding algorithms. In Fall 2025, I was a Software Engineering Intern with the TikTok Live Data BP Team (San Jose), where I worked on LLM-based data agents for business intelligence and large-scale analytics.
My research interests include statistical machine learning, optimal auction design, uncertainty quantification, reinforcement learning, and large language models. I am a member of the Lab for Statistics, Computing, Algorithms, Learning, and Economics (SCALE) at UCLA. Under the supervision of Prof. Xiaowu Dai, my research has focused on auction mechanism design and auto-bidding algorithms for online advertising, incorporating uncertainty quantification techniques. I have also explored variance reduction methods through experience replay in reinforcement learning, and examined large language models from a game-theoretic perspective.
News
03/2026: Paper on robust multi-item auction design accepted to the ICLR 2026 Workshop on AI for Mechanism Design and Strategic Decision Making.
01/2026: Paper on auto-bidding under return-on-spend constraints accepted to WWW 2026, conducted during my summer internship at JD.com.
11/2025: Paper on variance reduction via experience replay accepted to AAAI 2026 (Oral).
10/2025: Paper on distribution-free uncertainty quantification for online auction design accepted to JASA.
09/2025: Collaborative work on truthful language models accepted to NeurIPS 2025.
Publications
Online Auction Design Using Distribution-Free Uncertainty Quantification with Applications to E-Commerce. [journal][preprint][code]
Jiale Han and Xiaowu Dai.
Journal of the American Statistical Association (JASA), 2025.
Variance Reduction via Resampling and Experience Replay. [pdf][code]
Jiale Han, Xiaowu Dai, and Yuhua Zhu.
The 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026. (Oral Presentation, top 4.5%)
Auto-Bidding under Return-on-Spend Constraints with Uncertainty Quantification. [pdf][code]
Jiale Han, Chun Gan, Chengcheng Zhang, Jie He, Zhangang Lin, Ching Law, and Xiaowu Dai.
The ACM Web Conference (WWW), 2026.
A Robust Multi-Item Auction Design with Statistical Learning. [pdf][code]
Jiale Han and Xiaowu Dai.
ICLR Workshop on AI for Mechanism Design and Strategic Decision Making (ICLR Workshop AIMS), 2026.
Incentivizing Truthful Language Models via Peer Elicitation Games. [pdf][code]
Baiting Chen, Tong Zhu, Jiale Han, Leixn Li, Gang Li, and Xiaowu Dai.
Advances in Neural Information Processing Systems (NeurIPS), 2025.
Awards
Most Promising Statistician Award, UCLA, 2023
Statistics and Data Science Department Summer Mentored Research Fellowship, UCLA, 2023
Overseas Graduate Studies Fellowship, UCAS, 2021
Tang-Lixin Outstanding Student Leader Scholarship, UCAS, 2020
Outstanding Student Leader, UCAS, 2019