Institute for Computational and Mathematical Engineering (ICME)
Showing 81-100 of 172 Results
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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. -
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). -
Ali Mani
Professor of Mechanical Engineering
BioAli Mani is a professor of Mechanical Engineering at Stanford University. He is a faculty affiliate of the Institute for Computational and Mathematical Engineering at Stanford. He received his PhD in Mechanical Engineering from Stanford in 2009. Prior to joining the faculty in 2011, he was an engineering research associate at Stanford and a senior postdoctoral associate at Massachusetts Institute of Technology in the Department of Chemical Engineering. His research group builds and utilizes large-scale high-fidelity numerical simulations, as well as methods of applied mathematics, to develop quantitative understanding of transport processes that involve strong coupling with fluid flow and commonly involve turbulence or chaos. His teaching includes the undergraduate engineering math classes and graduate courses on fluid mechanics and numerical analysis.
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Alison Marsden
Douglass M. and Nola Leishman Professor of Cardiovascular Diseases, Professor of Pediatrics (Cardiology) and of Bioengineering and, by courtesy, of Mechanical Engineering
Current Research and Scholarly InterestsThe Cardiovascular Biomechanics Computation Lab at Stanford develops novel computational methods for the study of cardiovascular disease progression, surgical methods, and medical devices. We have a particular interest in pediatric cardiology, and use virtual surgery to design novel surgical concepts for children born with heart defects.
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Michaëlle Ntala Mayalu
Assistant Professor of Mechanical Engineering and, by courtesy, of Bioengineering
BioDr. Michaëlle N. Mayalu is an Assistant Professor of Mechanical Engineering. She received her Ph.D., M.S., and B.S., degrees in Mechanical Engineering at the Massachusetts Institute of Technology. She was a postdoctoral scholar at the California Institute of Technology in the Computing and Mathematical Sciences Department. She was a 2017 California Alliance Postdoctoral Fellowship Program recipient and a 2019 Burroughs Wellcome Fund Postdoctoral Enrichment Program award recipient. She is also a 2023 Hypothesis Fund Grantee.
Dr. Michaëlle N. Mayalu's area of expertise is in mathematical modeling and control theory of synthetic biological and biomedical systems. She is interested in the development of control theoretic tools for understanding, controlling, and predicting biological function at the molecular, cellular, and organismal levels to optimize therapeutic intervention.
She is the director of the Mayalu Lab whose research objective is to investigate how to optimize biomedical therapeutic designs using theoretical and computational approaches coupled with experiments. Initial project concepts include: i) theoretical and experimental design of bacterial "microrobots" for preemptive and targeted therapeutic intervention, ii) system-level multi-scale modeling of gut associated skin disorders for virtual evaluation and optimization of therapy, iii) theoretical and experimental design of "microrobotic" swarms of engineered bacteria with sophisticated centralized and decentralized control schemes to explore possible mechanisms of pattern formation. The experimental projects in the Mayalu Lab utilize established techniques borrowed from the field of synthetic biology to develop synthetic genetic circuits in E. coli to make bacterial "microrobots". Ultimately the Mayalu Lab aims to develop accurate and efficient modeling frameworks that incorporate computation, dynamical systems, and control theory that will become more widespread and impactful in the design of electro-mechanical and biological therapeutic machines.
