Adji Bousso Dieng
Princeton CS · Assistant Professor
Research focus: machine learning · computational biology · natural sciences · energy-based models
保护类第 1 项人工审核：作为科学领域 AI 类型的申请人，必须清晰展示概率建模、生成建模、energy-based models 以及科学领域 ai 动机。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: machine learning · computational biology).
- Applicants should prepare for a technically mathematical AI-for-science lab: probabilistic/generative modeling, energy-based models, diversity/mode-collapse, biological/material/environmental systems,
- 你想把 ML 接到真实数据与落地问题（当前信号：machine learning · computational biology）。
- 申请人应准备在具有数学技术背景的 AI 科学实验室：涉及概率生成建模、energy-based models、多样性/模式坍塌、生物/材料/环境系统以及独立科学面向的 ML 项目。
What to watch for / 什么情况下要慎重
- You want pure theory ML with little domain data or cross-disciplinary collaboration.
- 你要的是纯理论 ML、几乎不碰领域数据或跨学科合作。
Public evidence as of 2026-06-10
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