School of Engineering
Showing 301-400 of 444 Results
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Arogyaswami Paulraj
Professor (Research) of Electrical Engineering, Emeritus
BioProf. Arogyaswami Paulraj is an Emeritus Professor at Stanford University. Paulraj's legacy is deeply intertwined with the evolution of wireless communication. His groundbreaking work on MIMO (multiple input, multiple output) technology laid the foundation for today's ubiquitous 4G/5G networks and high-speed Wi-Fi.
Paulraj's journey began in the Indian Navy, where he served from 1965 to 1991. During this time, he led the development of the APSOH anti-submarine sonar system and established three key R&D labs for the Indian government. His contributions earned him the prestigious Padma Bhushan award, India's third highest civilian honor.
Following his naval career, Paulraj joined Stanford University as a postdoctoral researcher. His research focus shifted to wireless communication, where he made groundbreaking contributions to MIMO technology. MIMO enables data transmission using multiple antennas, significantly increasing network capacity and data rates.
Paulraj's innovation has been recognized with numerous accolades, including the 2024 Royal Acad. Eng. Prince Philip Medal, the 2023 IET Faraday Medal, the 2014 Marconi Prize, and the 2011 IEEE Alexander Graham Bell Medal. He is also a fellow of nine national academies in engineering, sciences, and the arts, and an inductee of the US Patent Office’s National Inventors Hall of Fame.
Currently, Paulraj continues to contribute to technological advancement. He chairs several committees for the Government of India, focusing on the Indian Semiconductor Mission and Core ICT initiatives. His dedication to research and development continues to shape the future of wireless communication. -
Marco Pavone
Associate Professor of Aeronautics and Astronautics, Senior Fellow at the Precourt Institute for Energy and Associate Professor, by courtesy, of Electrical Engineering & of Computer Science
BioDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University, where he directs the Autonomous Systems Laboratory and the Center for Automotive Research at Stanford. He is also a Distinguished Research Scientist at NVIDIA where he leads autonomous vehicle research. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a number of awards, including a Presidential Early Career Award for Scientists and Engineers from President Barack Obama, an Office of Naval Research Young Investigator Award, a National Science Foundation Early Career (CAREER) Award, a NASA Early Career Faculty Award, and an Early-Career Spotlight Award from the Robotics Science and Systems Foundation. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40. His work has been recognized with best paper nominations or awards at a number of venues, including the European Conference on Computer Vision, the IEEE International Conference on Robotics and Automation, the European Control Conference, the IEEE International Conference on Intelligent Transportation Systems, the Field and Service Robotics Conference, the Robotics: Science and Systems Conference, and the INFORMS Annual Meeting.
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Markus Pelger
Associate Professor of Management Science and Engineering and, by courtesy, of Finance at the Graduate School of Business
Current Research and Scholarly InterestsHis research focuses on understanding and managing financial risk. He develops mathematical financial models and statistical methods, analyzes financial data and engineers computational techniques. His research is divided into three streams: machine learning solutions to big-data problems in empirical asset pricing, statistical theory for high-dimensional data and stochastic financial modeling.
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Mert Pilanci
Associate Professor of Electrical Engineering
Current Research and Scholarly InterestsDr. Pilanci's research interests include neural networks, machine learning, mathematical optimization, information theory and signal processing.
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Peter Pinsky
Professor of Mechanical Engineering, Emeritus
BioPinsky works in the theory and practice of computational mechanics with a particular interest in multiphysics problems in biomechanics. His work uses the close coupling of techniques for molecular, statistical and continuum mechanics with biology, chemistry and clinical science. Areas of current interest include the mechanics of human vision (ocular mechanics) and the mechanics of hearing. Topics in the mechanics of vision include the mechanics of transparency, which investigates the mechanisms by which corneal tissue self-organizes at the molecular scale using collagen-proteoglycan-ion interactions to explain the mechanical resilience and almost perfect transparency of the tissue and to provide a theoretical framework for engineered corneal tissue replacement. At the macroscopic scale, advanced imaging data is used to create detailed models of the 3-D organization of collagen fibrils and the results used to predict outcomes of clinical techniques for improving vision as well as how diseased tissue mechanically degrades. Theories for mass transport and reaction are being developed to model metabolic processes and swelling in tissue. Current topics in the hearing research arena include multiscale modeling of hair-cell mechanics in the inner ear including physical mechanisms for the activation of mechanically-gated ion channels. Supporting research addresses the mechanics of lipid bilayer cell membranes and their interaction with the cytoskeleton. Recent past research topics include computational acoustics for exterior, multifrequency and inverse problems; and multiscale modeling of transdermal drug delivery. Professor Pinsky currently serves as Chair of the Mechanics and Computation Group within the Department of Mechanical Engineering at Stanford.
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Eric Pop
Pease-Ye Professor, Professor of Electrical Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Materials Science and Engineering and of Applied Physics
Current Research and Scholarly InterestsThe Pop Lab explores problems at the intersection of nanoelectronics and nanoscale energy conversion. These include fundamental limits of current and heat flow, energy-efficient transistors and memory, and energy harvesting via thermoelectrics. The Pop Lab also works with novel nanomaterials like carbon nanotubes, graphene, BN, MoS2, and their device applications, through an approach that is experimental, computational and highly collaborative.
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Robert Prakash
Chief Technology Officer & Chief Operating Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Technology Officer & Chief Operating Officer, Stanford Engineering | Center for Global & Online Education
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Adrienne Propp
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2021
BioI am a fourth year PhD student in ICME (the Institute for Computational and Mathematical Engineering). Prior to Stanford, I was working as a technical analyst at the RAND Corporation where I spent most of my time designing microsimulations and other models to investigate topics in healthcare, education, disaster relief, and international relations.
My research interests lie at the intersection of mathematics, data, and modeling, which has led me to a focus on scientific machine learning (SciML). Specifically, I am working on developing new graph-based surrogate modeling methods for low-data regimes. I am grateful to be advised by Daniel Tartakovsky, During my PhD, I have also collaborated with Jenny Suckale to model volcanic lava fountaining, and Susan Athey and Sanath Kumar Krishnamurthy to design improved algorithms for contextual bandits.
Past research projects have ranged from computational models of the heart to inverse modeling to predict satellite performance. -
Jian Qin
Associate Professor of Chemical Engineering
BioJian Qin is an Associate Professor in the Department of Chemical Engineering at the Stanford University. His research focuses on development of microscopic understanding of structural and physical properties of soft matters by using a combination of analytical theory, scaling argument, numerical computation, and molecular simulation. He worked as a postdoctoral scholar with Juan de Pablo in the Institute for Molecular Engineering at the University of Chicago and with Scott Milner in the Department of Chemical Engineering at the Pennsylvania State University. He received his Ph.D. in the Department of Chemical Engineering and Materials Science at the University of Minnesota under the supervision of David Morse and Frank Bates. His research covers self-assembly of multi-component polymeric systems, molecular origin of entanglement and polymer melt rheology, coacervation of polyelectrolytes, Coulomb interactions in dielectrically heterogeneous electrolytes, and surface charge polarizations in particulate aggregates in the absence or presence of flow.
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Priyanka Raina
Associate Professor of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsFor Priyanka's research please visit her group research page at https://stanfordaccelerate.github.io
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Ashwin Rao
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioMy current research and teaching is in Machine Learning (specifically RL) with applications to Financial Markets and Retail businesses. My academic origins are in Algorithms Theory and Abstract Algebra. More details on my background are here: https://www.linkedin.com/in/ashwin2rao/
My Stanford Home Page: https://stanford.edu/~ashlearn
CME 241 ("RL for Finance"), which I teach each Winter quarter: http://cme241.stanford.edu -
Juan Rivas-Davila
Associate Professor of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsModern applications demand power capabilities beyond what is presently achievable. High performance systems need high power density and bandwidth that are difficult to achieve.
Power density can be improved with better semiconductors and passive componets, and by reducing the energy storage requirements of the system. By dramatically increasing switching frequency it is possible to reduce size of power converters. I'm interested in high performance/frequency circuits switching >10 MHz. -
Judith Romero
Chief Communications Officer, Stanford Online and CGOE,, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Communications Officer for the Stanford Engineering Center for Global & Online Education (CGOE) and Stanford Online. Responsible for web and social media sites, for public information and media relations, and for brand strategy and global marketing.
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Noah Rosenberg
Stanford Professor of Population Genetics and Society
Current Research and Scholarly InterestsHuman evolutionary genetics, mathematical models in evolution and genetics, mathematical phylogenetics, statistical and computational genetics, theoretical population genetics
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Grant M. Rotskoff
Assistant Professor of Chemistry
BioGrant Rotskoff studies the nonequilibrium dynamics of living matter with a particular focus on self-organization from the molecular to the cellular scale. His work involves developing theoretical and computational tools that can probe and predict the properties of physical systems driven away from equilibrium. Recently, he has focused on characterizing and designing physically accurate machine learning techniques for biophysical modeling. Prior to his current position, Grant was a James S. McDonnell Fellow working at the Courant Institute of Mathematical Sciences at New York University. He completed his Ph.D. at the University of California, Berkeley in the Biophysics graduate group supported by an NSF Graduate Research Fellowship. His thesis, which was advised by Phillip Geissler and Gavin Crooks, developed theoretical tools for understanding nonequilibrium control of the small, fluctuating systems, such as those encountered in molecular biophysics. He also worked on coarsegrained models of the hydrophobic effect and self-assembly. Grant received an S.B. in Mathematics from the University of Chicago, where he became interested in biophysics as an undergraduate while working on free energy methods for large-scale molecular dynamics simulations.
Research Summary
My research focuses on theoretical and computational approaches to "mesoscale" biophysics. Many of the cellular phenomena that we consider the hallmarks of living systems occur at the scale of hundreds or thousands of proteins. Processes like the self-assembly of organelle-sized structures, the dynamics of cell division, and the transduction of signals from the environment to the machinery of the cell are not macroscopic phenomena—they are the result of a fluctuating, nonequilibrium dynamics. Experimentally probing mesoscale systems remains extremely difficult, though it is continuing to benefit from advances in cryo-electron microscopy and super-resolution imaging, among many other techniques. Predictive and explanatory models that resolve the essential physics at these intermediate scales have the power to both aid and enrich the understanding we are presently deriving from these experimental developments.
Major parts of my research include:
1. Dynamics of mesoscale biophysical assembly and response.— Biophysical processes involve chemical gradients and time-dependent external signals. These inherently nonequilibrium stimuli drive supermolecular organization within the cell. We develop models of active assembly processes and protein-membrane interactions as a foundation for the broad goal of characterizing the properties of nonequilibrium biomaterials.
2. Machine learning and dimensionality reduction for physical models.— Machine learning techniques are rapidly becoming a central statistical tool in all domains of scientific research. We apply machine learning techniques to sampling problems that arise in computational chemistry and develop approaches for systematically coarse-graining physical models. Recently, we have also been exploring reinforcement learning in the context of nonequilibrium control problems.
3. Methods for nonequilibrium simulation, optimization, and control.— We lack well-established theoretical frameworks for describing nonequilibrium states, even seemingly simple situations in which there are chemical or thermal gradients. Additionally, there are limited tools for predicting the response of nonequilibrium systems to external perturbations, even when the perturbations are small. Both of these problems pose key technical challenges for a theory of active biomaterials. We work on optimal control, nonequilibrium statistical mechanics, and simulation methodology, with a particular interest in developing techniques for importance sampling configurations from nonequilibrium ensembles. -
DANIELA RUANO
Affiliate, Stanford Engineering Center for Global and Online Education
BioArchitect and Project Leader with 10+ years of experience in high-impact real estate projects. Founder and Director of ADR, an architecture and design strategy studio leveraging BIM and Virtual Design & Construction (VDC) to align design, execution, and business value. Background in sustainable design, multidisciplinary leadership and academic teaching.
I hold a Master’s degree in Advanced Sustainable Design from the University of Edinburgh (UK) with LEED Green Associate certification. My professional interests lie at the intersection of design strategy, sustainability, and leadership. -
Amin Saberi
Professor of Management Science and Engineering and, by courtesy, of Computer Science
BioAmin Saberi is Professor of Management Science and Engineering at Stanford University. He received his B.Sc. from Sharif University of Technology and his Ph.D. from Georgia Institute of Technology in Computer Science. His research interests include algorithms, design and analysis of social networks, and applications. He is a recipient of the Terman Fellowship, Alfred Sloan Fellowship and several best paper awards.
Amin was the founding CEO and chairman of NovoEd Inc., a social learning environment designed in his research lab and used by universities such as Stanford as well as non-profit and for-profit institutions for offering courses to hundreds of thousands of learners around the world. -
Alberto Salleo
Hong Seh and Vivian W. M. Lim Professor, Professor of Photon Science, and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsNovel materials and processing techniques for large-area and flexible electronic/photonic devices. Polymeric materials for electronics, bioelectronics, and biosensors. Electrochemical devices for neuromorphic computing. Defects and structure/property studies of polymeric semiconductors, nano-structured and amorphous materials in thin films. Advanced characterization techniques for soft matter.
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Julia Salzman
Associate Professor of Biomedical Data Science, of Biochemistry and, by courtesy, of Statistics and of Biology
Current Research and Scholarly Interestsstatistical computational biology focusing on splicing, cancer and microbes
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Marc Sanders
Chief Compliance Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Compliance Officer, Stanford Engineering Center for Global & Online Education
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Krishna Saraswat
Rickey/Nielsen Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsNew and innovative materials, structures, and process technology of semiconductor devices, interconnects for nanoelectronics and solar cells.
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Michael Saunders
Professor (Research) of Management Science and Engineering, Emeritus
BioSaunders develops mathematical methods for solving large-scale constrained optimization problems and large systems of equations. He also implements such methods as general-purpose software to allow their use in many areas of engineering, science, and business. He is co-developer of the large-scale optimizers MINOS, SNOPT, SQOPT, PDCO, the dense QP and NLP solvers LSSOL, QPOPT, NPSOL, and the linear equation solvers SYMMLQ, MINRES, MINRES-QLP, LSQR, LSMR, LSLQ, LNLQ, LSRN, LUSOL.
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Samuel Seidel
Adjunct Professor, d.school
BioSam is the K12 Lab Director of Strategy + Research at the Stanford d.school, and co-author of Creative Hustle (Ten Speed Press, 2022), Changing the Conversation About School Safety (Stanford d.school, 2022), Hip Hop Genius 2.0 (Rowman & Littlefield, 2022), and Hip Hop Genius: Remixing High School Education (Rowman & Littlefield, 2011).
He speaks internationally about education, race, culture, systems, and design.
Sam graduated from Brown University with a degree in Education and a teaching certification, was a Visiting Practitioner at Harvard Graduate School of Education, a Scholar-in-Residence at Columbia University's Institute for Urban and Minority Education, and a Community Fellow at the Rhode Island School of Design. -
Debbie Senesky
Associate Professor of Aeronautics and Astronautics, of Electrical Engineering, Senior Fellow at the Precourt Institute for Energy and Associate Professor, by courtesy, of Photon Science
BioDebbie G. Senesky is an Associate Professor at Stanford University in the Aeronautics and Astronautics Department and the Electrical Engineering Department. In addition, she is the Principal Investigator of the EXtreme Environment Microsystems Laboratory (XLab). Her research interests include the development of nanomaterials for extreme harsh environments, high-temperature electronics for Venus exploration, and microgravity synthesis of nanomaterials. In the past, she has held positions at GE Sensing (formerly known as NovaSensor), GE Global Research Center, and Hewlett Packard. She received the B.S. degree (2001) in mechanical engineering from the University of Southern California. She received the M.S. degree (2004) and Ph.D. degree (2007) in mechanical engineering from the University of California, Berkeley. Prof. Senesky is the Site Director of nano@stanford. She is currently the co-editor of two technical journals: IEEE Journal of Microelectromechanical Systems and Sensors. In recognition of her research, she received the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2025, Emerging Leader Abie Award from AnitaB.org in 2018, Early Faculty Career Award from the National Aeronautics and Space Administration (NASA) in 2012, Gabilan Faculty Fellowship Award in 2012, and Sloan Ph.D. Fellowship from the Alfred P. Sloan Foundation in 2004.
Prof. Senesky's career path and research has been featured by Scientific American, Seeker, People Behind the Science podcast, The Future of Everything radio show, Space.com, and NPR's Tell Me More program. More information about Prof. Senesky can be found at https://xlab.stanford.edu and on Instagram (@astrodebs). -
Cory Shain
Assistant Professor of Linguistics and, by courtesy, of Psychology
BioI lead the Laboratory for Computation & Language in Minds & Brains (CLiMB Lab). We try to figure out how our brains let us go so efficiently from sensation (e.g., speech, reading) to meaning, and we do this using a combination of neuroimaging, computer modeling, and behavioral experiments. See the lab website for details.
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Eric S.G. Shaqfeh
Lester Levi Carter Professor and Professor of Mechanical Engineering
Current Research and Scholarly InterestsI have over 25 years experience in theoretical and computational research related to complex fluids following my PhD in 1986. This includes work in suspension mechanics of rigid partlcles (rods), solution mechanics of polymers and most recently suspensions of vesicles, capsules and mixtures of these with rigid particles. My research group is internationally known for pioneering work in all these areas.
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Ronie Shilo
Chief Education Initiatives Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordManaging Director, Programs Strategy and Development, Stanford Engineering Center for Global & Online Education
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Constantine Sideris
Associate Professor of Electrical Engineering
BioConstantine Sideris is an Associate Professor of Electrical Engineering at Stanford University. Previously, he was an Assistant Professor at the University of Southern California from 2018 to 2025 and an Associate Professor from 2025 to 2026. He received the B.S., M.S., and Ph.D. degrees with honors from the California Institute of Technology in 2010, 2011, and 2017 respectively. He was a visiting scholar at UC Berkeley’s Wireless Research Center from 2013 to 2014. He was a postdoctoral fellow in the departments of Electrical Engineering and Computing and Mathematical Sciences at Caltech from January 2017 to August 2018.
He was the recipient of an ONR YIP award in 2023, an NSF CAREER award in 2021, an AFOSR YIP award in 2020, an AFOSR DURIP award in 2021, the Caltech Leadership Award in 2017, and an NSF graduate research fellowship in 2010. His research is highly interdisciplinary and bridges the fields of bioengineering, medicine, applied mathematics and computation with electrical engineering and physics.
His research interests include analog/RF integrated circuits, photonic integrated circuits, and computational electromagnetics for biomedical and biosensing applications and wireless communications. His current interests in biomedical devices include portable Point-of-Care in-vitro biosensors, wearable devices for real-time monitoring and analysis of biological signals, ingestible “smart” pills, and implantable devices. His current interests in computational electromagnetics include developing fast algorithms for simulating RF and nanophotonic devices and coupling them with efficient optimization algorithms to achieve the automated design of new, high-performance electromagnetic devices. -
Aaron Sidford
Associate Professor of Management Science and Engineering and of Computer Science
Current Research and Scholarly InterestsMy research interests lie broadly in the optimization, the theory of computation, and the design and analysis of algorithms. I am particularly interested in work at the intersection of continuous optimization, graph theory, numerical linear algebra, and data structures.
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Karin Sligar
Programs & Administration Manager, Stanford SystemX Alliance
Current Role at StanfordPrograms & Administration Manager, SystemX Alliance
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Olav Solgaard
Audrey S. Hancock Professor in the School of Engineering
BioThe Solgaard group focus on design and fabrication of nano-photonics and micro-optical systems. We combine photonic crystals, optical meta-materials, silicon photonics, and MEMS, to create efficient and reliable systems for communication, sensing, imaging, and optical manipulation.
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Shuran Song
Assistant Professor of Electrical Engineering
BioShuran Song is an Assistant Professor of Electrical Engineering at Stanford University. Before joining Stanford, she was faculty at Columbia University. Shuran received her Ph.D. in Computer Science at Princeton University, BEng. at HKUST. Her research interests lie at the intersection of computer vision and robotics. Song’s research has been recognized through several awards, including the Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21, RSS’19, and finalists at RSS, ICRA, CVPR, and IROS. She is also a recipient of the NSF Career Award, Sloan Foundation fellowship as well as research awards from Microsoft, Toyota Research, Google, Amazon, and JP Morgan.
To learn more about Shuran’s work, please visit: https://shurans.github.io/ -
Andrew Spakowitz
Senior Associate Dean for Research and Faculty Affairs, Professor of Chemical Engineering, of Materials Science and Engineering and, by courtesy, of Applied Physics
Current Research and Scholarly InterestsTheory and computation of biological processes and complex materials
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Adrien Specht-Wyss
Ph.D. Student in Computational and Mathematical Engineering, admitted Spring 2024
BioI'm a PhD student in the Institute for Computational and Mathematical Engineering (ICME) at Stanford University, mentored by Prof. Mignot. My research is at the intersection of artificial intelligence and sleep medicine, focusing on developing predictive models for circadian rhythms and sleep debt from proteomics data. I adopt a problem-oriented approach, selecting methods based on the data and research questions at hand. My techniques range from linear regression to sophisticated deep learning frameworks, aiming to extract maximal insights from the data. I also explore the use of unsupervised and semi-supervised learning, and am interested in the applications of multimodal and foundation models in biology.
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Jenny Suckale
Associate Professor of Geophysics and, Senior Fellow, by courtesy, at the Woods Institute for the Environment
BioMy research group studies disasters to reduce the risk they pose. We approach this challenge by developing customized mathematical models that can be tested against observational data and are informed by community needs through a scientific co-production process. We intentionally work on extremes across different natural systems rather than focusing on one specific natural system to identify both commonalities in the physical processes driving extremes and in the best practices for mitigating risk at the community level. Our current research priorities include volcanic eruptions, ice-sheet instability, permafrost disintegration, induced seismicity and flood-risk mitigation. I was recently awarded the Presidential Early Career Awards for Scientists and Engineers, the highest honor bestowed by the United States Government on science and engineering professionals in the early stages of their independent research careers and the CAREER award from the National Science Foundation.
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Thierry Tambe
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioThierry Tambe is an Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science, and the William George and Ida Mary Hoover Faculty Fellow at Stanford University. His research centers on co-designing algorithms and hardware—from high-level models down to custom silicon—to enable efficient execution of AI and data-intensive workloads, with memory efficiency as a central theme. His work has been recognized through an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, an NVIDIA Graduate PhD Fellowship, an IEEE SSCS Predoctoral Achievement Award, and several distinguished paper awards. Previously, Thierry was a visiting research scientist at NVIDIA and an engineer at Intel. He received a B.S. and M.Eng. from Texas A&M University, and a PhD from Harvard University, all in Electrical Engineering.
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Sindy Tang
Associate Professor of Mechanical Engineering, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Radiology and of Bioengineering
Current Research and Scholarly InterestsProf. Sindy K.Y. Tang develops engineering platforms that measure biological systems and convert these measurements into quantitative datasets. Her research focuses on experimental systems that probe biological processes across cellular and tissue scales, particularly how physical context—geometry, mechanics, and spatial organization—shapes biological function. Current work spans immune diagnostics, spatial tissue sampling for multi-omics analysis, and single-cell perturbation studies.
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Daniel Tartakovsky
Professor of Energy Science Engineering
Current Research and Scholarly InterestsEnvironmental fluid mechanics, Applied and computational mathematics, Biomedical modeling.
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Hamdi Tchelepi
Max Steineke Professor and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsCurrent research activities: (1) model and simulate unstable miscible and immiscible fluid flow in heterogeneous porous media, (2) develop multiscale numerical solution algorithms for coupled mechanics and multiphase fluid flow in large-scale subsurface formations, and (3) develop stochastic solution methods that quantify the uncertainty associated with predictions of fluid-structure dynamics in porous media.
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Caroline Trippel
Assistant Professor of Computer Science and of Electrical Engineering
BioCaroline Trippel is an Assistant Professor in the Computer Science and Electrical Engineering Departments at Stanford University, where she leads the High Assurance Computer Architectures Lab. Following her PhD, prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Trippel's research fits broadly in the area of computer architecture and focuses on promoting high assurance—correctness, security, and reliability—as a first-order computer architecture design goal. A central theme of her work is leveraging formal methods, especially automated reasoning, techniques to design and verify hardware systems. Trippel research has influenced the design of the RISC-V ISA memory consistency model both via her formal analysis of its draft specification and her subsequent participation in the RISC-V Memory Model Task Group; prompted Intel to update their Software Security Guidance to confirm that two Intel microarchitectures satisfy assumptions made by the Seberus Spectre defense that her lab developed; and produced a novel methodology and tool that synthesized two new variants of the famous Meltdown and Spectre attacks. Trippel's research has been recognized with IEEE Top Picks distinctions, a Sloan Research Fellowship, an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, the Intel Rising Star Faculty Award, an Intel Outstanding Researcher Award, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering, and more.
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Madeleine Udell
Associate Professor of Management Science and Engineering
Current Research and Scholarly InterestsProfessor Udell builds the mathematical and computational foundations needed for
scalable, accessible, and responsible data-driven decisionmaking in high-stakes domains, with impact on challenges in healthcare, finance, marketing, operations, and engineering.
She develops new efficient algorithms to accelerate and automate optimization and data science, and new frameworks that empower users to invoke these algorithms and interpret the resulting decisions. -
Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering and, by courtesy, of Computer Science
BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department's Graduate Teaching Award, and the Lanchester Prize. He was the plenary speaker at the 2019 Allerton Conference on Communications, Control, and Computing. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen. -
Andras Vasy
Robert Grimmett Professor of Mathematics
Current Research and Scholarly InterestsMy research concentrates on topics in two broad areas of applications of microlocal analysis in which, partly with collaborators, I introduced new ideas in recent years: non-elliptic linear and non-linear partial differential equations (PDE), typically concerning wave propagation or other related phenomena, and inverse problems for X-ray type transforms along geodesics and related problems for determining the metric tensor from boundary measurements.
