Stanford University
Showing 201-300 of 455 Results
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Peter K. Kitanidis
Professor of Civil and Environmental Engineering
BioKitanidis develops methods for the solution of interpolation and inverse problems utilizing observations and mathematical models of flow and transport. He studies dilution and mixing of soluble substances in heterogeneous geologic formations, issues of scale in mass transport in heterogeneous porous media, and techniques to speed up the decay of pollutants in situ. He also develops methods for hydrologic forecasting and the optimization of sampling and control strategies.
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Fredrik Kjolstad
Assistant Professor of Computer Science
BioFredrik Kjolstad is an Assistant Professor in Computer Science at Stanford University. He works on topics in compilers, programming models, and systems, with an emphasis on compiler techniques that make high-level languages portable. He has received the NSF CAREER Award, the MIT EECS Sprowls PhD Thesis Award in Computer Science, the Tau Beta Phi 2024 Teaching Honor Roll, the Google ML and Systems Junior Faculty Awards, and several distinguished paper awards.
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Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics, Senior Fellow at the Stanford Institute for Human-Centered AI and Associate Professor, by courtesy, of Computer Science
BioMykel Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is an author of "Decision Making under Uncertainty: Theory and Application" (2015), "Algorithms for Optimization" (2019), and "Algorithms for Decision Making" (2022), all from MIT Press. He is a third generation pilot.
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Ava Kouhana
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2024
BioHi ! I am an ICME master's degree student at Stanford University, currently conduction research in Professor Gordon Wetzstein’s Computational Imaging Lab.
Prior to Stanford, I dedicated six months conducting research at Harvard under the supervision of Dr. Mengyu Wang, focusing primarily on Computer Vision tasks like Image Segmentation and Vision-Language Models. Before joining ICME , I have had the opportunity to work for six months supervised by Stanford Professor Craig Levin, researching the application of Diffusion Models for image super-resolution.
My research interests primarily revolve around computer vision, deep learning, and generative AI, with a growing interest for 3D modeling and video generation. -
Christoforos Kozyrakis
Leonard Bosack and Sandy K. Lerner Professor of Engineering and Professor of Computer Science
BioChristos Kozyrakis is the Leonard Bosack and Sandy K. Lerner Professor of Engineering and a Professor of Electrical Engineering and Computer Science at Stanford University. His primary research areas are computer architecture and computer systems. His current work focuses on cloud computing, systems for machine learning, and machine learning for systems.
Christos holds a BS degree from the University of Crete and a PhD degree from the University of California at Berkeley. He is a fellow of the ACM and the IEEE. He has received the ACM SIGARCH Maurice Wilkes Award, the ISCA Influential Paper Award, the NSF Career Award, the Okawa Foundation Research Grant, and faculty awards by IBM, Microsoft, and Google. -
Ellen Kuhl
Catherine Holman Johnson Director of Stanford Bio-X, Walter B Reinhold Professor in the School of Engineering, Professor of Mechanical Engineering and, by courtesy, of Bioengineering
Current Research and Scholarly Interestscomputaitonal simulation of brain development, cortical folding, computational simulation of cardiac disease, heart failure, left ventricular remodeling, electrophysiology, excitation-contraction coupling, computer-guided surgical planning, patient-specific simulation
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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. -
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). -
Carissa Little
Associate Dean and Executive Director, Stanford Engineering Center for Global and Online Education
Current Role at StanfordAssociate Dean, Global and Online Education, School of Engineering
Executive Director, Center for Global and Online Education and Stanford Online -
Ming Luo
Associate Director for Global Engineering Programs, Global Engineering Programs
Current Role at StanfordAs the associate director of Global Engineering Programs, Ming is managing several School of Engineering programs including UGVR, Global Engineering Internship, etc.
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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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Andrew J. Mannix
Assistant Professor of Materials Science and Engineering
Current Research and Scholarly InterestsAtomically thin 2D materials incorporated into van der Waals heterostructures are a promising platform to deterministically engineer quantum materials with atomically resolved thickness and abrupt interfaces across macroscopic length scales while retaining excellent material properties. Because 2D materials exhibit a wide range of electronic characteristics with properties that often rival conventional electronic materials — e.g., metals, semiconductors, insulators, and superconductors — it is possible to combine them in virtually infinite variety to achieve diverse heterostructures. Furthermore, the van der Waals interface enables interlayer twist engineering to modify the interlayer symmetry, periodic potential (moiré superlattice), and hybridization, which has resulted in novel quantum states of matter. Many of these heterostructures, especially those involving specific interlayer twist angles, would be otherwise infeasible through direct growth.
The Mannix Group is developing a unique set of in-house capabilities to systematically elucidate the fundamental structure-property relationships underpinning the growth of 2D materials and their inclusion into van der Waals heterostructures. Greater understanding will allow us to provide a platform for engineering the properties of matter at the atomic scale and offer guidance for emerging applications in novel electronics and in quantum information science.
To accomplish this, we employ: precise growth techniques such as chemical vapor deposition and molecular beam epitaxy; automated van der Waals assembly; and atomically-resolved microscopy including cryo-STM/AFM. -
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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Todd Martinez
David Mulvane Ehrsam and Edward Curtis Franklin Professor of Chemistry and Professor of Photon Science
Current Research and Scholarly InterestsAb initio molecular dynamics, photochemistry, molecular design, mechanochemistry, graphical processing unit acceleration of electronic structure and molecular dynamics, automated reaction discovery, ultrafast (femtosecond and attosecond) chemical phenomena
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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. -
Paul McIntyre
Rick and Melinda Reed Professor, Professor of Photon Science and Senior Fellow at the Precourt Institute for Energy
BioMcIntyre's group performs research on nanostructured inorganic materials for applications in electronics, energy technologies and sensors. He is best known for his work on metal oxide/semiconductor interfaces, ultrathin dielectrics, defects in complex metal oxide thin films, and nanostructured Si-Ge single crystals. His research team synthesizes materials, characterizes their structures and compositions with a variety of advanced microscopies and spectroscopies, studies the passivation of their interfaces, and measures functional properties of devices.
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Subhasish Mitra
William E. Ayer Professor of Electrical Engineering and Professor of Computer Science
BioSubhasish Mitra holds the William E. Ayer Endowed Chair Professorship in the Departments of Electrical Engineering and Computer Science at Stanford University. He directs the Stanford Robust Systems Group, serves on the leadership team of the Microelectronics Commons AI Hardware Hub funded by the US CHIPS and Science Act, leads the Computation Focus Area of the Stanford SystemX Alliance, and is the Associate Chair (Faculty Affairs) of Computer Science. His research ranges across Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences. Results from his research group have influenced almost every contemporary electronic system and have inspired significant government and research initiatives in multiple countries. He has held several international academic appointments — the Carnot Chair of Excellence in NanoSystems at CEA-LETI in France, Invited Professor at EPFL in Switzerland, and Visiting Professor at the University of Tokyo in Japan. Prof. Mitra also has consulted for major technology companies including AMD (XIlinx), Cisco, Google, Intel, Merck (EMD Electronics), and Samsung.
In the field of Robust Computing, he has created many key approaches for circuit failure prediction, CASP on-line diagnostics, QED system validation, soft error resilience, and X-Compact test compression. Their adoption by industry is growing rapidly, in markets ranging from cloud computing to automotive systems, under various names (Silicon Lifecycle Management, Predictive Health Monitoring, In-System Test Architecture, In-field Scan, In-fleet Scan). His X-Compact approach has proven essential to cost-effective manufacturing and high-quality testing of almost all 21st century systems. X-Compact and its derivatives enabled billions of dollars of cost savings across the industry.
In the field of NanoSystems, with his students and collaborators, he demonstrated several firsts: the first NanoSystems hardware among all beyond-silicon nanotechnologies for energy-efficient computing (the carbon nanotube computer), the first 3D NanoSystem with computation immersed in data storage, the first published end-to-end computing systems using resistive memories (Resistive RAM-based non-volatile computing systems delivering 10-fold energy efficiency versus embedded flash), and the first monolithic 3D integration combining heterogeneous logic and memory technologies in silicon foundry. These received wide recognition: cover of NATURE, several Highlights to the US Congress, and highlight as "important scientific breakthrough" by news organizations worldwide.
Prof. Mitra's honors include the Harry H. Goode Memorial Award (by IEEE Computer Society for outstanding contributions in the information processing field), Newton Technical Impact Award in EDA (test-of-time honor by ACM SIGDA and IEEE CEDA), the University Researcher Award (by Semiconductor Industry Association and Semiconductor Research Corporation to recognize lifetime research contributions), the EDAA Achievement Award (by European Design and Automation Association, for outstanding lifetime contributions to electronic design, automation and testing), the Intel Achievement Award (Intel’s highest honor), and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur. He and his students have published over 15 award-winning papers across 5 topic areas (technology, circuits, EDA, test, verification) at major venues including the Design Automation Conference, International Electron Devices Meeting, International Solid-State Circuits Conference, International Test Conference, Symposia on VLSI Technology/VLSI Circuits, and Formal Methods in Computer-Aided Design. Stanford undergraduates have honored him several times "for being important to them." He is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and a Foreign Member of Academia Europaea. -
Ariam Mogos
Lecturer
BioAriam Mogos leads emerging technology initiatives at Stanford's Hasso Plattner Institute of Design (d.school), where she helps students and educators work with emerging technologies like AI and blockchain, and shapes conversations around the tech’s ethical implications on humans and nature. Her design work and research also investigates the ways that technology can foster playful learning experiences that bridge communities and cultures.
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Parviz Moin
Franklin P. and Caroline M. Johnson Professor in the School of Engineering
BioMoin is the founding director of the Center for Turbulence Research. Established in 1987 as a research consortium between NASA and Stanford, Center for Turbulence Research is devoted to fundamental studies of turbulent flows. Center of Turbulence Research is widely recognized as the international focal point for turbulence research, attracting diverse groups of researchers from engineering, mathematics and physics. He was the founding director of the Institute for Computational and Mathematical Engineering at Stanford.
Professor Moin pioneered the use of direct and Large Eddy Simulation techniques for the study of turbulence physics, control and modelling concepts and has written widely on the structure of turbulent shear flows. His current interests include: Computational physics, Physics and control of turbulent boundary layers, hypersonic flows, propulsion, flow control, large eddy simulation for aerospace applications and aircraft icing. -
Pedram Mokrian
Lecturer
Instructor, Stanford Engineering Center for Global and Online EducationBioPedram Mokrian is Adjunct Professor at Stanford University and a lecturer at the Haas School of business at UC Berkeley where he teaches and advises entrepreneurs and global 1000 companies alike on entrepreneurship, business model disruption, and technology innovation strategy. He was previously a Principal at Mayfield, one of Silicon Valley’s most storied venture capital firms, where he was part of the investment team with over $3.5B assets under management. Mokrian is a founding Partner of the Ratio Academy, New Line Ventures. He also serves as a mentor or advisor to a number of start-ups, innovation incubators, including Global Innovation Catalyst, the Texas Medical Center Innovation Center, Innovation Labs, MISO, and Moog, and serves on the advisory board of Phillips66.
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Louie Montoya
Lecturer
BioA self-proclaimed deeper learning education nerd, Louie Montoya joined the d.school in 2018 to work with educators on learning and implementing design in the classroom. Today he leads the Deeper Learning Puzzle Bus, a K12 lab mobile experiment designed to look at how “escape rooms” can change the way educators think about measurement and assessment, as well as bring more delight into the classroom.
A first generation Mexican American raised across the western hemisphere, Louie developed an interest in other cultures that anchors his work on behalf of equitable practices in the design process. As an experience designer at the Business Innovation Factory in Rhode Island, Louie co-designed and ran the Teachers for Equity Fellowship that worked with educators across the United States to address issues of racial inequity in their schools and classrooms. As a member of the Deeper Learning network Louie focuses on building capacity around skills such as collaboration, communication and critical thinking with students. -
Walter Murray
Professor (Research) of Management Science and Engineering, Emeritus
BioProfessor Murray's research interests include numerical optimization, numerical linear algebra, sparse matrix methods, optimization software and applications of optimization. He has authored two books (Practical Optimization and Optimization and Numerical Linear Algebra) and over eighty papers. In addition to his University work he has extensive consulting experience with industry, government, and commerce.
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Sanjiv Narayan
Professor of Medicine (Cardiovascular Medicine)
Current Research and Scholarly InterestsDr. Narayan directs the Computational Arrhythmia Research Laboratory, whose goal is to define the mechanisms underlying complex human heart rhythm disorders, to develop bioengineering-focused solutions to improve therapy that will be tested in clinical trials. The laboratory has been funded continuously since 2001 by the National Institutes of Health, AHA and ACC, and interlinks a disease-focused group of clinicians, computational physicists, bioengineers and trialists.
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Brett Newman
Lecturer
BioAcademic
2013 - 2018 : Stanford : Lecturer : Visual Thinking, ME115C: Design and Business Factors
2018 - Present : Stanford : Lead Lecturer : Design 161 Capstone
Professional
2004 - 2007 : Azud : VP Product
2007 - Present : Daylight Design : Partner -
Simona Onori
Associate Professor of Energy Science Engineering and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsModeling, control and optimization of dynamic systems;
Model-based control in advanced propulsion systems;
Energy management control and optimization in HEVs and PHEVs;
Energy storage systems- Li-ion and PbA batteries, Supercapacitors;
Battery aging modeling, state of health estimation and life prediction for control;
Damage degradation modeling in interconnected systems -
Brad Osgood
Professor of Electrical Engineering and, by courtesy, in Education
BioOsgood is a mathematician by training and applies techniques from analysis and geometry to various engineering problems. He is interested in problems in imaging, pattern recognition, and signal processing.
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Julia Palacios
Associate Professor of Statistics and of Biomedical Data Science
BioDr. Palacios’s research spans Bayesian nonparametrics, probabilistic AI, stochastic processes, and computational statistics. Her group develops stochastic models and efficient inference algorithms for understanding evolutionary dynamics in population genetics, infectious diseases and cancer.
