School of Engineering
Showing 1-10 of 16 Results
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Ching-Yao Lai
Assistant Professor of Geophysics
BioMy group attacks fundamental questions in geophysics and fluid dynamics 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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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.
