Institute for Computational and Mathematical Engineering (ICME)
Showing 1-17 of 17 Results
-
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.
-
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.
-
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
-
Wei Li
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioDr. Wei Li works at the intersection of AI strategy, governance, and enterprise impact.
Wei is an AI executive and Adjunct Professor at Stanford University, focusing on Innovation to Impact (I2I)—turning computational, AI, and interdisciplinary ideas into deployable systems, scalable products, and measurable business, societal and clinical outcomes.
Previously, Wei served as VP/GM of AI & Analytics (AIA) at Intel, leading large global teams that built full-stack AI software platforms and shaping AI product strategy, ecosystem development, and enterprise deployment at scale, driving multi-billion-dollar AI revenue across enterprise and industry use cases. He also previously served on the boards of the PyTorch Foundation and Linux Foundation AI&Data, contributing to open-source governance, industry collaboration, and responsible AI adoption. Wei has collaborated with leading technology companies including Meta, OpenAI, Google, Microsoft, Hugging Face, AWS, and Accenture, as well as emerging startups. He has delivered keynotes and lectures at leading forums, including the World AI Summit and Harvard Business School, and engage with media such as Bloomberg to share insights on AI strategy, governance, and enterprise impact.
Wei regularly advises executives and boards on AI strategy, governance, and risk management—particularly where AI materially affects competitiveness, scale, and regulatory exposure. Wei holds a Ph.D. in Computer Science from Cornell University and completed an executive program at Stanford Graduate School of Business. -
Christian Linder
Professor of Civil and Environmental Engineering
BioChristian Linder is a Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering. Through the development of novel and efficient in-house computational methods based on a sound mathematical foundation, the research goal of the Computational Mechanics of Materials (CM2) Lab at Stanford University, led by Dr. Linder, is to understand micromechanically originated multi-scale and multi-physics mechanisms in solid materials undergoing large deformations and fracture. Applications include sustainable energy storage materials, flexible electronics, and granular materials.
Dr. Linder received his Ph.D. in Civil and Environmental Engineering from UC Berkeley, an MA in Mathematics from UC Berkeley, an M.Sc. in Computational Mechanics from the University of Stuttgart, and a Dipl.-Ing. degree in Civil Engineering from TU Graz. Before joining Stanford in 2013 he was a Junior-Professor of Micromechanics of Materials at the Applied Mechanics Institute of Stuttgart University where he also obtained his Habilitation in Mechanics. Notable honors include a Fulbright scholarship, the 2013 Richard-von-Mises Prize, the 2016 ICCM International Computational Method Young Investigator Award, the 2016 NSF CAREER Award, and the 2019 Presidential Early Career Award for Scientists and Engineers (PECASE).
