Mengdi Wang is an associate professor at the Department of Electrical Engineering and Center for Statistics and Machine Learning at Princeton University. She is also affiliated with the Department of Computer Science and a visiting research scientist at DeepMind. Her research focuses on data-driven stochastic optimization and applications in machine and reinforcement learning. She received her PhD in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 2013. At MIT, Mengdi was affiliated with the Laboratory for Information and Decision Systems and was advised by Dimitri P. Bertsekas. 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. She spent her sabbatical year as a senior visiting research scientist at Google Deepmind in 2019-2020. She serves as an associate editor for Operations Research and Mathematics of Operations Research, as area chair for ICML, NeurIPS, AISTATS, and is on the editorial board of Journal of Machine Learning Research.