Navid Assistant Azizan

Navid Assistant Azizan is an Associate Professor in the Department of Mechanical Engineering at the Massachusetts Institute of Technology. His research interests include AI, machine learning, and intelligent systems, as well as control, optimization, and autonomous systems. He is also engaged in dynamics, networks, and sociotechnical systems. Azizan's work has been recognized with several awards, including the Joseph A. Martore (1975) Excellence in Teaching Award and the National Science Foundation CAREER Award. He holds a Ph.D. from California Institute of Technology and has held positions at Stanford University and Google DeepMind.

Navid Azizan is an Alfred H. (1929) and Jean M. Hayes Assistant Professor at MIT, specializing in Trustworthy Autonomy, AI, and Learning for Control. His research focuses on developing robust and reliable AI systems for control applications, emphasizing decisions under uncertainty and signals and systems. Azizan's work includes advancing continual learning, distributed optimization, and meta-learning for nonlinear systems. He explores methods such as orthogonal gradient descent, stochastic mirror descent, and adaptive control, aiming to enhance the stability and performance of AI-driven systems. His research also addresses challenges in deep learning, including out-of-distribution detection and implicit regularization.