Dr. Andrej Risteski

Andrej Risteski is an assistant professor in the Department of Machine Learning at Carnegie Mellon University. Before his position at Carnegie Mellon, Andrey was a Norbert Wiener Fellow in the Department of Applied Mathematics at MIT, as well as at the Institute for Data Science and Statistics (IDSS). Andrey holds a Ph.D. in Computer Science from Princeton University, where he also earned his bachelor's degree.
His research area is the mathematical and scientific foundations of machine learning and artificial intelligence, with a particular focus on deep learning and neural networks. Andrej regularly publishes in top machine learning conferences (NeurIPS, ICML, ICLR), as well as in theoretical computer science (STOC, COLT). He also regularly serves on the program and review committees for these conferences. 

NSF (Medium) I1S-2211907: Foundations of Self-Supervised Learning Through the Lens of Probabilistic Generative Models 

Amazon Research Award: Causal + Deep Out-of-Distribution Learning

CMU/Price Waterhouse (PwC) Digital Transformation and Innovation Center: Robust and Fair AT Systems in Dynamic Environments