Petros Koumoutsakos
Harvard SEAS CS · Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering
Research focus: scientific machine learning · computational science · fluid mechanics · bioinspired robotics
手动审核申请准备：作为科学计算 / 科学型 ML 申请人：数值 eth 模、fluid mechanics、active matter、bioinspired robotics、优化或基于生理 cs 学习的学习。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: scientific machine learning · computational science).
- Applicants should be prepared for physics-informed computation: numerical methods, fluid mechanics, optimization/control, scientific ML, and high-performance computing, with willingness to work at the
- 你想把 ML 接到真实数据与落地问题（当前信号：scientific machine learning · computational science）。
- 申请人应准备好基于生理cs信息化的计算：数值eth模、fluid mechanics、优化与控制、科学ML以及高性能计算，并愿意在AI与物理系统之间工作。
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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