Mengdi Wang | |
|---|---|
| Alma mater | Massachusetts Institute of Technology Tsinghua University |
| Scientific career | |
| Institutions | Princeton University |
| Thesis | Stochastic methods for large-scale linear problems, variational inequalities, and convex optimization (2013) |
| Doctoral advisor | Dimitri Bertsekas |
Mengdi Wang is a theoretical computer scientist who is a professor at Princeton University. Her research considers the fundamental theory that underpins reinforcement and machine learning. She was named one of MIT Technology Review's 35 Under 35 in 2018.