Michael Kearns
Penn CIS / Penn Engineering AI · National Center Professor of Management & Technology; Founding Director, Warren Center for Network and Data Sciences
Research focus: machine learning theory · algorithmic game theory · responsible AI · computational social science
手动审核申请准备：构建基于 ML 理论的拟合参数图，围绕 algorithmic game theory、responsible AI、computational social science 及网络科学进行建模；引用一个可见于实验室主题、校友/就业模式、基准信号、当前学生名单、招募/状态警告或项目领域，并提出一项具体的第一学期研究扩展。
Who this advisor fits / 什么情况下适合你
- You want theory depth and proof/analysis-oriented problem framing.
- You care about faculty-track outcomes; public alumni rows include verifiable faculty placements.
- A high-bar theory/responsible-AI target: applicants should show mathematical maturity and read recent/current group topics before assuming availability.
- 你要的是理论深度、证明/分析导向的问题设定。
- 你在意学术教职/教职轨去向，公开校友里有可核对的教职案例。
- 高标准的理论/负责任目标：申请人应展示深厚的数学素养，并熟悉近期或当前领域顶刊论文，在做出假设前审慎评估其可解释性。
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.
- 你只想做快速 benchmark / API 拼装，不想读领域论文或做长期实验。
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.