People

Sanjay Lall is Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He received a B.A. degree in Mathematics with first-class honors in 1990 and a Ph.D. degree in Engineering in 1995, both from the University of Cambridge, England. His research group focuses on algorithms for control, optimization, and machine learning. From 2018 to 2019 he was Director in the Autonomous Systems Group at Apple. Before joining Stanford he was a Research Fellow at the California Institute of Technology in the Department of Control and Dynamical Systems, and prior to that he was a NATO Research Fellow at Massachusetts Institute of Technology, in the Laboratory for Information and Decision Systems. He was also a visiting scholar at Lund Institute of Technology in the Department of Automatic Control. He has significant industrial experience applying advanced algorithms to problems including satellite systems, advanced audio systems, Formula 1 racing, the America’s cup, cloud services monitoring, and integrated circuit diagnostic systems, in addition to several startup companies. Professor Lall has served as Associate Editor for the journal Automatica, on the steering and program committees of several international conferences, and as a reviewer for the National Science Foundation, DARPA, and the Air Force Office of Scientific Research. He is the author of over 130 peer-refereed publications. He is currently a visiting researcher and director at Google.

Amirhossein Afsharrad is a PhD student in Electrical Engineering. His research focuses on reinforcement learning and bandits. Amirhossein is interested in optimization, control theory, and their applications in machine learning.

Emi Soroka is a PhD candidate in Aeronautics and Astronautics. Her research focuses on using signal temporal logic to improve motion planning for autonomous vehicles in long-tail situations. Emi is interested in optimization, solvers, and software architecture, and is the main developer of Satisfiability.jl: a Julia package for interacting with SMT solvers. She is an active member of the graduate community, having served on student advisory committees and as a social event planner in the Aero/Astro department. When not conducting research, she enjoys climbing and hanging out with friends.

Andrei Kanavalau is a PhD candidate in Electrical Engineering. His research focuses on augmenting control algorithms with machine learning while preserving safety and stability guarantees.

Nick Landolfi is a Ph.D. candidate in the Computer Science department at Stanford. He received a B.S. in Electrical Engineering & Computer Science with honors at the University of California, Berkeley in 2018. His research focuses on algorithms for control, optimization and machine learning.

Rohan Sinha is a PhD candidate in Aeronautics and Astronautics. His research focuses on developing methodologies that improve the reliability of ML-enabled robotic systems, particularly when these systems encounter out-of-distribution conditions with respect to their training data. Broadly, his research interests lie at the intersection of control theory, machine learning, and applied robotics. As an undergraduate, Rohan worked on data-driven predictive control under Prof. Francesco Borrelli in the Model Predictive Control Lab and on learning control algorithms that rely on vision systems under Prof. Benjamin Recht in the Berkeley Artificial Intelligence Lab. He has also interned as an autonomous driving engineer at Delphi (now Motional) and as a software engineer at Amazon. Rohan is co-advised by Prof. Sanjay Lall and Prof. Marco Pavone, who runs the Stanford Autonomous Systems Lab.