Electrical Engineering
Showing 361-380 of 793 Results
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Renesmee Kuo
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioRenesmee Kuo is an Electrical Engineering PhD candidate at Stanford University supported by NSF GRFP and Stanford Lieberman fellowship. Her research interests lie at the intersection of engineering and medicine. She focuses on validation of preclinical PET imaging tracers and their translation into the clinic for applications in neuroinflammatory diseases (e.g., MS, AD) and cancer (e.g., brain metastasis) in Prof. Michelle James' lab. She graduated from UC Berkeley with a BS in Bioengineering. At Berkeley, she worked in Prof. Steve Conolly's lab on Magnetic Particle Imaging (MPI), focusing on tracking CAR-T cells in immunotherapy using high-resolution MPI tracers. She also explored commercially-available high-resolution MPI tracers for early diagnosis of pulmonary embolisms and cardiovascular disease in preclinical settings.
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Sanjay Lall
Professor of Electrical Engineering
BioSanjay Lall is Professor of Electrical Engineering in the Information Systems Laboratory and Professor of Aeronautics and Astronautics 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. 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.
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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering, Professor of Computer Science and, by courtesy, of Electrical Engineering
BioProfessor Lam's current research interest is to create effective and reliable AI assistants to accelerate the discovery of knowledge. Her OVAL lab has created numerous open-source LLM-based tools used by consumers, historians, and journalists in their work; currently, she is focusing on research assistants that can discover new insights for biomedicine and other technical areas.
Professor Lam's team has created the first quantifiably factual and engaging conversational agent, which has won the Best Research of the Year Award from Wikimedia Foundation; pioneered deep research agent called STORM that has been used by about a million users; developed the best-performing agent for retrieving knowledge from hybrid sources, including databases, knowledge graphs, and free-text, currently deployed at Wikimedia; created an agent framework that produces fluent task-oriented agents that do not hallucinate.
Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”. She was on the founding team of Tensilica, now a part of Cadence.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow. -
Hannah Lee
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
Masters Student in Electrical Engineering, admitted Winter 2026Current Research and Scholarly InterestsComputational Neuroscience, Statistical Modeling for Neuroscience
