- Robust methods
- Generative models
- Convex and nonconvex optimization
- Distributed optimization
Yaoliang Yu is currently an associate professor in the David R. Cheriton School of Computer Science at University of Waterloo. He obtained his PhD from the computing science department of University of Alberta in 2013, and he spent two wonderful postdoctoral years at CMU. His main research interests include robust regression and classification, representation learning, kernel methods, generative models, convex and nonconvex optimization, distributed system, and applications in computer vision, natural languages, and finance.
- PhD Dissertation Award from the Canadian Artificial Intelligence Association, 2015
- Top reviewers for ICML/NeurIPS, 2018
- ACM SIGSOFT Distinguished Paper Award 2020