Rajesh Ranganath
NYU — Courant Institute CS + Center for Data Science (CDS) · Associate Professor of CS & DS
Research focus: probabilistic ML · Bayesian inference · ML for health/causal · generative models
保护项目 2 的预审审核：构建基于概率机器的模型，在 Rajesh Ranganath 上构建概率机器的拟合曲线，在 rag 上构建概率机器的拟合曲线，在 chi 上构建概率机器的拟合曲线，在 ML 上构建概率机器的拟合曲线，在 ai 上构建概率机器的拟合曲线。请提及一个最近的项目或论文，并说明您可以在第一学期开始实施的第一个具体扩展。
Who this advisor fits / 什么情况下适合你
- Strong probabilistic-ML fit; applicants should bring a mature probabilistic modeling artifact and directly ask about recent alumni outcomes.
- 强概率拟合 ML 良好；申请人应携带成熟的概率建模成果，并直接询问近期校友的绩效表现。
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.