School of Engineering
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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.
Postdoctoral Research Fellow, Electrical Engineering
BioGuénolé Lallement received the M.Sc. degree (Hons.) in analog and digital IC design from Imperial College London, London, U.K., in 2016, and the Engineering Diploma degree in electronic and computer science from Télécom ParisTech, Paris, France. In 2019, he completed his Ph.D. degree with the IM2NP Institute, Aix-Marseille University and STMicroelectronics, Crolles, France, under the co-supervision of Prof. J.-L. Autran and Dr. F. Abouzeid.
At Imperial College London and under the supervision of Dr. P. Georgiou, he worked on creating bio-inspired CMOS DNA microarray. This project received the Hertha Ayrtan Centenary Prize for the best M.Sc. project with significant original contribution to the topic area. His thesis research interests include the extension of SoCs mission capabilities by offering near-zero-power performances and enabling continuous functionality for IoT systems.
In 2020, he started a postdoctoral position at Stanford with Prof. Subhasish Mitra and Prof. Boris Murmann. His research focuses on system-level design and optimal computing organization - 3D vs 2D - for specific computing domains using emerging technologies.
Anand Vikas Lalwani
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
Masters Student in Electrical Engineering, admitted Spring 2020
BioAnand is a Graduate Student researcher in XLab (advisor: Debbie Senesky).
Anand's research work includes developing and deploying sensors for environmental and energy industries. Sensors developed include techniques for Hall Effect sensors to measure AC magnetic fields, deployable and low cost ammonia sensor for rivers and lakes, CO2 sensors for down-hole applications.
Anand's interests outside of research include startups and solving problems. Anand is committed to developing technologies that tackle pressing issues and translating work form lab into a startup.
Professor of Computer Science, & by courtesy, of Electrical Engineering
BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford MobiSocial Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.
Professor Lam’s research mission is to disrupt the status quo where centralized monopoly platforms are prevalent and consumers privacy is compromised. This challenging problem led her to ten years of research in many disciplines in computer science: natural language processing, machine learning, compilers, distributed systems, and human-computer interaction. She advocates the development of open-source virtual assistants that users can “program” in natural language; these assistants should be federated to give users choice and to support sharing without a centralized third party. Her research prototype demonstrates a viable open-source alternative to the emerging oligopoly of virtual assistants.
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”.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow.