Han Shao
University of Maryland CS · Assistant Professor
Research focus: machine learning theory · economics and computation · algorithmic game theory · human-AI interaction
手动审核申请准备：以Han Shao理论/经济学与计算申请人身份准备：学习理论、协作学习激励、human-AI interaction、鲁棒性或生成模型可评估性。
Who this advisor fits / 什么情况下适合你
- You want theory depth and proof/analysis-oriented problem framing.
- Applicants should bring rigorous ML theory/game theory evidence and use the homepage recruiting note as the primary admissions signal, not alumni outcomes.
- 你要的是理论深度、证明/分析导向的问题设定。
- 申请人应提交严谨的 ML 理论或博弈论证据，并以此作为主要录取信号，而非校友结果。
What to watch for / 什么情况下要慎重
- You only want fast benchmarks/API hacking, not domain papers or longer experimental loops.
- You need strong placement evidence, but public signals for this PI are still thin.
- 你只想做快速 benchmark / API 拼装，不想读领域论文或做长期实验。
- 你需要强证据的毕业去向分布，而这位 PI 目前公开信号仍较薄。
Public evidence as of 2026-06-10
These are decision-support signals compiled from public evidence (faculty pages, publications, lab sites) to help you ask better questions — not a ranking, rating, or allegation about this advisor. / 以上为基于公开信息整理的择校参考，帮助你提出更好的问题，并非排名、评分或对该导师的指控。
Ask a verified 学长学姐 / 同校 .edu 认证点评
The thing applicants say only 师兄师姐 can tell you — current & former students of this lab, verified by their school .edu. Open the full dossier to read or add a verified note.