Andrej Risteski is an Assistant Professor at the Machine Learning Department in Carnegie Mellon University. Prior to that, he was a Norbert Wiener Research Fellow jointly in the Applied Math department and IDSS at MIT. He received my PhD in the Computer Science Department at Princeton University under the advisement of Sanjeev Arora. His research interests lie in the intersection of machine learning, statistics, and theoretical computer science, spanning topics like (probabilistic) generative models, algorithmic tools for learning and inference, representation and self-supervised learning, out-of-distribution generalization and applications of neural approaches to natural language processing and scientific domains. More broadly, the goal of his research is principled and mathematical understanding of statistical and algorithmic problems arising in modern machine learning paradigms.