School of Engineering
Showing 1-20 of 29 Results
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Ching-Yao Lai
Assistant Professor of Geophysics
BioMy group attacks fundamental questions in fluid dynamics and geophysics by integrating mathematical and machine-learned models with observational data. We use our findings to address challenges facing the world, such as advancing our scientific knowledge of ice dynamics under climate change. The length scale of the systems we are interested in varies broadly from a few microns to thousands of kilometers, because the governing physical principles are often universal across a range of length and time scales. We use mathematical models, simulations, and machine learning to study the complex interactions between fluids and elasticity and their interfacial dynamics, such as multiphase flows, flows in deformable structures, and cracks. We extend our findings to tackle emerging topics in climate science and geophysics, such as understand the missing physics that governs the flow of ice sheets in a warming climate. We welcome collaborations across disciplinary lines, from geophysics, engineering, physics, applied math to computer science, since we believe combining expertise and methodologies across fields is crucial for new discoveries.
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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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Thomas Lee
Professor of Electrical Engineering
BioProfessor Lee's principal areas of professional interest include analog circuitry of all types, ranging from low-level DC instrumentation to high-speed RF communications systems. His present research focus is on CMOS RF integrated circuit design, and on extending operation into the terahertz realm.
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Sanjiva Lele
Edward C. Wells Professor of the School of Engineering and Professor of Mechanical Engineering
BioProfessor Lele's research combines numerical simulations with modeling to study fundamental unsteady flow phemonema, turbulence, flow instabilities, and flow-generated sound. Recent projects include shock-turbulent boundary layer interactions, supersonic jet noise, wind turbine aeroacoustics, wind farm modeling, aircraft contrails, multi-material mixing and multi-phase flows involving cavitation. He is also interested in developing high-fidelity computational methods for engineering applications.
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Adrian Lew
Professor of Mechanical Engineering
BioProf. Lew's interests lie in the broad area of computational solid mechanics. He is concerned with the fundamental design and mathematical analysis of material models and numerical algorithms.
Currently the group is focused on the design of algorithms to simulate hydraulic fracturing. To this end we work on algorithms for time-integration embedded or immersed boundary methods. -
Zetian Li
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2024
Current Research and Scholarly InterestsStatistical Learning, Machine Learning, Bayesian Statistics, Probability Theory
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Wei Li
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioDr. Wei Li is an accomplished AI software executive and Adjunct Professor in ICME at Stanford University. Known for scaling cutting-edge innovation into multi-billion dollar businesses, he previously served as the VP/GM of AI Software Engineering at Intel. Dr. Li also shapes the global AI ecosystem as a board member for both the PyTorch Foundation and the Linux Foundation AI&Data, and has advised numerous AI startups. He holds a Ph.D. in Computer Science from Cornell University.
Executive Impact and Commercialization: In the last decade, Wei led teams that developed full stack AI software, models, solutions, and co-designing AI hardware, which contributed to generating multi-billion-dollar AI revenue for Intel. His teams earned five Intel Achievement Awards. On performance and scale, improved AI performance by 10-100X through software acceleration of frameworks and libraries, secured the #1 ranking for 7B LLMs on Hugging Face, and supported training a 1 trillion-parameter model with Argonne National Laboratory on a 60,000-GPU supercomputer. On products, built enterprise ready AI solutions, co-designed AI-accelerated CPU/GPUs, and integrated advanced optimizations into the most popular software frameworks such as PyTorch with 100M+ annual downloads.
Ecosystem Leadership and Influence: Wei forged collaborations with Meta (PyTorch, Llama), OpenAI (Triton), Google (TensorFlow), Microsoft (DeepSpeed), Hugging Face, Accenture, and AI startups. He delivered keynotes and insights at Fortune, Bloomberg, World AI Summit, Forbes, GITEX, London AI Summit, VentureBeat, ZDNet, DataMakers Fest, New York AI Summit, and Milken Institute. Wei lectured on AI at Stanford, Harvard Business School, University of Texas-Austin, University of Chicago, University of Salerno, Technion - Israel Institute of Technology, Sapienza University of Rome, and University of Lisbon.
