Tengyu Ma

Tengyu Ma is an Assistant Professor of Computer Science and Statistics at Stanford University. His research interests broadly include topics in machine learning and algorithms, such as non-convex optimization, deep learning and its theory, reinforcement learning, representation learning, distributed optimization, convex relaxation (e.g. sum of squares hierarchy), and high-dimensional statistics. He received my Ph.D. from the Computer Science Department at Princeton University where he was advised by Professor Sanjeev Arora. As an undergrad, Tengyu Ma studied at Andrew Chi-Chih Yao's CS pilot class at Tsinghua University.

Teaching

• Statistical/Machine Learning Theory
• Machine Learning
• Introduction to Nonparametric Statistics

Awards

• 2022 Samsung AI Researcher of the Year
• Sloan Research Fellowships 2021
• NSF CAREER Award
• ACM Doctoral Dissertation Award Honorable Mention 2018
• COLT Best Paper Award 2018
• NIPS Best Student Paper Award 2016
• Siebel Scholarship
• Princeton Honorific Fellowship
• 8th Place in William Lowell Putnam Mathematical Competition 2010
• Silver Medal in International Mathematical Olympiad (IMO) 2007