Mengdi Wang
Assistant Professor of Operations Research and Financial Engineering
Office: 226 Sherrerd Hall
Phone: 609-258-8773
Interdisciplinary Research Area: Applied Math, Data Science, Financial Technology
Research Area: Decision making and reinforcement learning problems involving uncertainty or hidden information; modeling uncertainty and designing algorithmic approaches that "learn" the best decisions as information is revealed. optimization (stochastic, online, and even more), stochastic programming, variational inequalities, dynamic programing, statistical learning, and game dynamics.
Areas of Impact
Data Science
Data science accelerates discovery across nearly all areas of science, engineering, and social science. Students and faculty in this area create new data-analysis techniques and harness advanced computing and storage systems to solve problems in biology, the environment, materials science, communications, security, transportation, and many other areas.
Robotics and Cyberphysical Systems
The use of robots is moving rapidly beyond controlled environments such as factories to complex environments in the midst of human activity, demanding a nimble cross-disciplinary approach. Princeton engineers are advancing the productive, safe, and ethical use of robotics in society by building and connecting expertise in sensing, artificial intelligence, neuroscience, public policy, and other fields.
Primary affiliation
Operations Research and Financial Engineering
The Department of Operations Research and Financial Engineering is unique in the United States, combining deep roots in mathematics with engineering, business, and finance. Much of the research in the department focuses on developing mathematical and computational tools for making decisions under uncertainty. Work by faculty and students helps manage risk, optimize performance of complex systems, and manage resources efficiently. Expertise include “big data” analysis and financial technology (FinTech).
