Sanjay Krishnan
University of Chicago CS · Assistant Professor of Computer Science
Research focus: data governance · data provenance · AI in healthcare · data systems
人工审核申请准备：申请人应展示数据系统与应用领域 ML 的深度：data provenance、治理、清洁、医疗 AI，或那些能够确保数据移动可审计且安全的系统。
Who this advisor fits / 什么情况下适合你
- Applicants should show data-systems and applied-ML depth: data provenance, governance, cleaning, healthcare AI, or systems that make data movement auditable and safe.
- 申请人应展示数据系统与应用层面的深度：data provenance、治理、清洗、医疗AI，或那些能够确保数据移动可审计且安全的系统。
What to watch for / 什么情况下要慎重
- You need strong placement evidence, but public signals for this PI are still thin.
- 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.