Mengdi Wang is associate professor at the Center for Statistics and Machine Learning, Department of Electrical and Computer Engineering, Department of Computer Science (by courtesy) and the Omenn-Darling Bioengineering Institute (by courtesy) at Princeton University. Mengdi got her PhD in EECS from MIT in 2013, where she worked with Dimitri P. Bertsekas at the Laboratory for Information and Decision Systems. She was a visiting research scientist at DeepMind, Institute of Advanced Studies, and Simons Institute on Theoretical Computer Science. Her research focuses on reinforcement learning, generative AI and AI for science applications. 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 served as a Program Chair for ICLR 2023 and Senior AC for Neurips, ICML and COLT, and associate editor for Harvard Data Science Review.
研究方向
Reinforcement Learning in RoboticsAdvanced Bandit Algorithms ResearchStochastic Gradient Optimization TechniquesSparse and Compressive Sensing TechniquesMachine Learning and Algorithms
