Professor Kaizheng Wang, Assistant Professor of Industrial Engineering and Operations Research, recently received the IMS Tweedie New Researcher Award.
Presented by the Institute of Mathematical Statistics (IMS), the Tweedie Award is a prestigious early-career honor recognizing outstanding research contributions in statistics and related areas. As part of this honor, Professor Wang will be delivering the Tweedie New Researcher Invited Lecture at the IMS New Researchers Conference.
Professor Wang develops mathematical and computational methods for learning from related problems, discovering structure in complex data, and solving challenging optimization problems, including in settings where data are incomplete or distributed. His work has advanced our ability to extract meaningful patterns from complex data and to adapt to unknown variation across individuals, data sources, and time.
Professor Wang was selected "For (his) seminal contributions to learning from heterogeneous data, particularly in developing sharp theory and efficient methods for latent variable models and in establishing principled approaches for adaptive data integration under complex distribution shifts. For broad contributions to transfer learning, clustering, and uncertainty quantification.”
