Associate Professor of Electrical and Computer Engineering and the Center for Statistics and Machine Learning
Associated Faculty in Computer Science, Affiliated Faculty to Omenn-Darling Institute of Bioengineering

Mengdi Wang is an associate professor at the Department of Electrical and Computer Engineering and Center for Statistics and Machine Learning at Princeton University. She is also affiliated with the Department of Computer Science, Princeton’s ML Theory Group. She was a visiting research scientist at DeepMind, IAS and Simons Institute on Theoretical Computer Science. Her research focuses on machine learning, reinforcement learning, generative AI, AI for science and intelligence system applications . Mengdi received her PhD in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 2013, where she was affiliated with the Laboratory for Information and Decision Systems and advised by Dimitri P. Bertsekas. Before that, she got her bachelor degree from the Department of Automation, Tsinghua University. Mengdi received the Young Researcher Prize in Continuous Optimization of the Mathematical Optimization Society in 2016 (awarded once every three years), the Princeton SEAS Innovation Award in 2016, the NSF Career Award in 2017, the Google Faculty Award in 2017,  and the MIT Tech Review 35-Under-35 Innovation Award (China region) in 2018, WAIC YunFan Award 2022, AACC’s Donald Eckman Award 2024. She serves as a Program Chair for ICLR 2023 and Senior AC for Neurips, ICML, COLT, associate editor for Harvard Data Science Review, Operations Research. Research supported by NSF, AFOSR, NIH, ONR, Google, Microsoft C3.ai, FinUP, RVAC Medicines.

Mengdi’s research group studies machine learning theory, reinforcement learning, generative artificial intelligence, AI for science and intelligence system applications.