Kamyar's research interest is mainly in the area of Machine Learning, from theory to practice. He works on topics including but not limited to Reinforcement Learning (Bandits to MPDs, POMDPs, etc), Applied Mathematics, Deep Learning, Neural Operators, Control Theory, Spectral Method, Optimization, High Dimensional Statistics, Risk Assessment, Online learning, Domain Shift, Active Learning, Safety, Adversarial Attacks, and Generative models through both learning theory and core scientific lenses.
Kamyar is a Senior Research Scientist at Nvidia since Summer 2022. Prior to his role at Nvidia, he was an assistant professor at Purdue University, department of computer science, from Fall 2020 to Fall 2022. Prior to his faculty position, he was at the California Institute of Technology (Caltech) as a Postdoctoral Scholar in the Department of Computing + Mathematical Sciences.</p>
Before his postdoctoral position, he was appointed as a special student researcher at Caltech, working with ML and Control researchers at the CMS department and the Center for Autonomous Systems and Technologies. He is also a former visiting student researcher at Caltech. Kamyar Azizzadenesheli is a former visiting student researcher at Stanford University, and researcher at Simons Institute, UC. Berkeley. In addition, he is a former guest researcher at INRIA France (SequeL team), as well as a visitor at Microsoft Research Lab, New England, and New York. He received his Ph.D. at the University of California, Irvine.
