School of Engineering


Showing 1-50 of 138 Results

  • Sara Achour

    Sara Achour

    Assistant Professor of Computer Science and of Electrical Engineering

    Current Research and Scholarly InterestsI am an Assistant Professor jointly appointed to both the Computer Science and the Electrical Engineering Departments at Stanford University. My research focuses on new techniques and tools, specifically new programming languages, compilers, and runtime systems, that enable end-users to more easily develop computations that exploit the potential of emerging computing platforms that exhibit analog behaviors.

  • Alex Aiken

    Alex Aiken

    Alcatel-Lucent Professor of Communications and Networking and Professor of Particle Physics and Astrophysics

    BioAlex Aiken is the Alcatel-Lucent Professor of Computer Science at Stanford. Alex received his Bachelors degree in Computer Science and Music from Bowling Green State University in 1983 and his Ph.D. from Cornell University in 1988. Alex was a Research Staff Member at the IBM Almaden Research Center (1988-1993) and a Professor in the EECS department at UC Berkeley (1993-2003) before joining the Stanford faculty in 2003. His research interest is in areas related to programming languages.

  • Juan Alonso

    Juan Alonso

    Vance D. and Arlene C. Coffman Professor and the James and Anna Marie Spilker Chair of the Department of Aeronautics and Astronautics

    BioProf. Alonso is the founder and director of the Aerospace Design Laboratory (ADL) where he specializes in the development of high-fidelity computational design methodologies to enable the creation of realizable and efficient aerospace systems. Prof. Alonso’s research involves a large number of different manned and unmanned applications including transonic, supersonic, and hypersonic aircraft, helicopters, turbomachinery, and launch and re-entry vehicles. He is the author of over 200 technical publications on the topics of computational aircraft and spacecraft design, multi-disciplinary optimization, fundamental numerical methods, and high-performance parallel computing. Prof. Alonso is keenly interested in the development of an advanced curriculum for the training of future engineers and scientists and has participated actively in course-development activities in both the Aeronautics & Astronautics Department (particularly in the development of coursework for aircraft design, sustainable aviation, and UAS design and operation) and for the Institute for Computational and Mathematical Engineering (ICME) at Stanford University. He was a member of the team that currently holds the world speed record for human powered vehicles over water. A student team led by Prof. Alonso also holds the altitude record for an unmanned electric vehicle under 5 lbs of mass.

  • Amin Arbabian

    Amin Arbabian

    Associate Professor of Electrical Engineering

    Current Research and Scholarly InterestsMy group's research covers RF circuits and system design for (1) biomedical, (2) sensing, and (3) Internet of Things (IoT) applications.

  • Manan Arya

    Manan Arya

    Assistant Professor of Aeronautics and Astronautics

    Current Research and Scholarly InterestsManan Arya leads the Morphing Space Structures Laboratory. His research is on structures that can adapt their shape to respond to changing requirements. Examples include deployable structures for spacecraft that can stow in constrained volumes for launch and then unfold to larger sizes in space, terrestrial structures with variable geometry, and morphing robots. Key research thrusts include lightweight fiber-reinforced composite materials to enable innovative designs for flexible structures, and the algorithmic generation of the geometry of morphing structures – the arrangement of stiff and compliant elements – to enable novel folding mechanisms.

    He has published more than 20 journal and conference papers and has been awarded 5 US patents. Prior to joining Stanford, he was a Technologist at the Advanced Deployable Structures Laboratory at the Jet Propulsion Laboratory, California Institute of Technology, where he developed and tested breakthrough designs for space structures, including deployable reflectarrays, starshades, and solar arrays.

  • Jeremy Bailenson

    Jeremy Bailenson

    Thomas More Storke Professor, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Education
    On Leave from 10/01/2023 To 06/30/2024

    BioJeremy Bailenson is founding director of Stanford University’s Virtual Human Interaction Lab, Thomas More Storke Professor in the Department of Communication, Professor (by courtesy) of Education, Professor (by courtesy) Program in Symbolic Systems, and a Senior Fellow at the Woods Institute for the Environment. He has served as Director of Graduate Studies in the Department of Communication for over a decade. He earned a B.A. from the University of Michigan in 1994 and a Ph.D. in cognitive psychology from Northwestern University in 1999. He spent four years at the University of California, Santa Barbara as a Post-Doctoral Fellow and then an Assistant Research Professor.

    Bailenson studies the psychology of Virtual and Augmented Reality, in particular how virtual experiences lead to changes in perceptions of self and others. His lab builds and studies systems that allow people to meet in virtual space, and explores the changes in the nature of social interaction. His most recent research focuses on how virtual experiences can transform education, environmental conservation, empathy, and health. He is the recipient of the Dean’s Award for Distinguished Teaching at Stanford. In 2020, IEEE recognized his work with “The Virtual/Augmented Reality Technical Achievement Award”.

    He has published more than 200 academic papers, spanning the fields of communication, computer science, education, environmental science, law, linguistics, marketing, medicine, political science, and psychology. His work has been continuously funded by the National Science Foundation for over 25 years.

    His first book Infinite Reality, co-authored with Jim Blascovich, emerged as an Amazon Best-seller eight years after its initial publication, and was quoted by the U.S. Supreme Court. His new book, Experience on Demand, was reviewed by The New York Times, The Wall Street Journal, The Washington Post, Nature, and The Times of London, and was an Amazon Best-seller.

    He has written opinion pieces for The Washington Post, The Wall Street Journal, Harvard Business Review, CNN, PBS NewsHour, Wired, National Geographic, Slate, The San Francisco Chronicle, TechCrunch, and The Chronicle of Higher Education, and has produced or directed six Virtual Reality documentary experiences which were official selections at the Tribeca Film Festival. His lab has exhibited VR in hundreds of venues ranging from The Smithsonian to The Superbowl.

  • Biondo Biondi

    Biondo Biondi

    Barney and Estelle Morris Professor
    On Leave from 09/01/2023 To 08/31/2024

    Current Research and Scholarly InterestsResearch
    My students and I devise new algorithms to improve the imaging of reflection seismic data. Images obtained from seismic data are the main source of information on the structural and stratigraphic complexities in Earth's subsurface. These images are constructed by processing seismic wavefields recorded at the surface of Earth and generated by either active-source experiments (reflection data), or by far-away earthquakes (teleseismic data). The high-resolution and fidelity of 3-D reflection-seismic images enables oil companies to drill with high accuracy for hydrocarbon reservoirs that are buried under two kilometers of water and up to 15 kilometers of sediments and hard rock. To achieve this technological feat, the recorded data must be processed employing advanced mathematical algorithms that harness the power of huge computational resources. To demonstrate the advantages of our new methods, we process 3D field data on our parallel cluster running several hundreds of processors.

    Teaching
    I teach a course on seismic imaging for graduate students in geophysics and in the other departments of the School of Earth Sciences. I run a research graduate seminar every quarter of the year. This year I will be teaching a one-day short course in 30 cities around the world as the SEG/EAGE Distinguished Instructor Short Course, the most important educational outreach program of these two societies.

    Professional Activities
    2007 SEG/EAGE Distinguished Instructor Short Course (2007); co-director, Stanford Exploration Project (1998-present); founding member, Editorial Board of SIAM Journal on Imaging Sciences (2007-present); member, SEG Research Committee (1996-present); chairman, SEG/EAGE Summer Research Workshop (2006)

  • Stephen Boyd

    Stephen Boyd

    Samsung Professor in the School of Engineering

    BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University, and a member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.

    Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).

    Professor Boyd is the author of many research articles and four books: Introduction to Applied Linear Algebra: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with El Ghaoui, Feron, and Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.

    He has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, for excellence in computational mathematical programming. In 2023, he was given the AACC Richard E. Bellman Control Heritage Award, the highest recognition of professional achievement for U.S. control systems engineers and scientists. He is a Fellow of the IEEE, SIAM, INFORMS, and IFAC, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, a foreign member of the Chinese Academy of Engineering, and a foreign member of the National Academy of Engineering of Korea. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.

    He has developed and taught many undergraduate and graduate courses, including Signals & Systems, Linear Dynamical Systems, Convex Optimization, and a recent undergraduate course on Matrix Methods. His graduate convex optimization course attracts around 300 students from more than 20 departments. In 1991 he received an ASSU Graduate Teaching Award, and in 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering. In 2003, he received the AACC Ragazzini Education award, for contributions to control education. In 2016 he received the Walter J. Gores award, the highest award for teaching at Stanford University. In 2017 he received the IEEE James H. Mulligan, Jr. Education Medal, for a career of outstanding contributions to education in the fields of interest of IEEE, with citation "For inspirational education of students and researchers in the theory and application of optimization."

  • Leticia Britos Cavagnaro

    Leticia Britos Cavagnaro

    Adjunct Professor

    BioLeticia Britos Cavagnaro, Ph.D., is a scientist turned designer with a knack for creating transformative learning experiences. She holds a Ph.D. in Developmental Biology from Stanford's School of Medicine, and is a former member of the Research in Education & Design Lab (REDlab) from Stanford’s School of Education. She is the co-founder and co-Director of the University Innovation Fellows, a program of the Hasso Plattner Institute of Design (d.school), which empowers students to be co-designers of their education in collaboration with faculty and leaders at their schools. Leticia was the founding Deputy Director of the National Center for Engineering Pathways to Innovation (Epicenter), an NSF-funded initiative that operated from 2011 to 2016 to foster innovation and entrepreneurship in engineering education across the United States. Leticia works with educators from hundreds of schools and across disciplines in transforming their teaching practices by applying design abilities and pedagogical levers through the Teaching and Learning Studio program of the d.school. In addition, she works with corporate, non-profit and education leaders in the US and abroad in exploring how design can embolden leadership and drive responsible innovation. Leticia teaches Advanced Reflective Practice and Capstone Project to graduate students from Stanford’s Design Impact MS program, and uses emerging technologies to empower learners to be self-directed, action-oriented, and reflective shapers of the future. She was born in Uruguay, grew up in Colombia, and lives in San Francisco with her husband.

    Connect with Leticia:
    LinkedIn: linkedin.com/pub/leticia-britos-cavagnaro/9/b4a/752/
    Twitter: @LeticiaBritosC (twitter.com/leticiabritosc)

  • Emmanuel Candes

    Emmanuel Candes

    Barnum-Simons Chair of Math and Statistics, and Professor of Statistics and, by courtesy, of Electrical Engineering

    BioEmmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, a professor of electrical engineering (by courtesy) and a member of the Institute of Computational and Mathematical Engineering at Stanford University. Earlier, Candès was the Ronald and Maxine Linde Professor of Applied and Computational Mathematics at the California Institute of Technology. His research interests are in computational harmonic analysis, statistics, information theory, signal processing and mathematical optimization with applications to the imaging sciences, scientific computing and inverse problems. He received his Ph.D. in statistics from Stanford University in 1998.

    Candès has received several awards including the Alan T. Waterman Award from NSF, which is the highest honor bestowed by the National Science Foundation, and which recognizes the achievements of early-career scientists. He has given over 60 plenary lectures at major international conferences, not only in mathematics and statistics but in many other areas as well including biomedical imaging and solid-state physics. He was elected to the National Academy of Sciences and to the American Academy of Arts and Sciences in 2014.

  • Gunnar Carlsson

    Gunnar Carlsson

    Ann and Bill Swindells Professor, Emeritus

    BioDr. Carlsson has been a professor of mathematics at Stanford University since 1991. In the last ten years, he has been involved in adapting topological techniques to data analysis, under NSF funding and as the lead PI on the DARPA “Topological Data Analysis” project from 2005 to 2010. He is the lead organizer of the ATMCS conferences, and serves as an editor of several Mathematics journals

  • Carissa Carter

    Carissa Carter

    Adjunct Professor

    BioCarissa Carter is the Academic Director at the Stanford d.school. In this role she guides the development of the d.school’s pedagogy, leads its instructors, and shapes its class offerings. She teaches courses on the intersection of data and design, design for climate change, design for emerging tech, and maps and the visual sorting of information.

  • John M. Cioffi

    John M. Cioffi

    Hitachi America Professor in the School of Engineering, Emeritus

    BioJohn M. Cioffi teaches Stanford's graduate electrical engineering course sequence in digital communications, part-time as recalled emeritus presently, from 1986 to the present. Cioffi's research interests are in the theory of transmitting the highest possible data rates on a number of different communications channels, many of which efforts spun out of Stanford through he and/or his many former PhD students to companies, most notably including the basic designed globally used 500 million DSL connections. Cioffi also oversaw the prototype developments for the worlds first cable modem and digital-audio broadcast systems. Cioffi pioneering the use of remote management algorithms to improve (over the internet or cloud) both wireline (DSL) and wireless (Wi-Fi) physical-layer transmission performance, an area often known as Dynamic Spectrum Management or Dynamic Line Management. Cioffi is co-inventor on basic patents for vectored DSL transmission and optimized MIMO wireless transmission. In his early career, Cioffi developed the worlds first full-duplex voiceband data modem while at Bell Laboratories, and the worlds first adaptively equalized disk read channel while at IBM. His courses and research projects over the years center on the area of multiuser transmission methods.

  • Eric Darve

    Eric Darve

    Professor of Mechanical Engineering

    Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for engineering, surrogate and reduced order modeling, stochastic inversion, anomaly detection for engineering processes and manufacturing, numerical linear algebra, high-performance and parallel computing, and GPGPU.

  • David Donoho

    David Donoho

    Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences

    BioDavid Donoho is a mathematician who has made fundamental contributions to theoretical and computational statistics, as well as to signal processing and harmonic analysis. His algorithms have contributed significantly to our understanding of the maximum entropy principle, of the structure of robust procedures, and of sparse data description.

    Research Statement:
    My theoretical research interests have focused on the mathematics of statistical inference and on theoretical questions arising in applying harmonic analysis to various applied problems. My applied research interests have ranged from data visualization to various problems in scientific signal processing, image processing, and inverse problems.

  • Ron Dror

    Ron Dror

    Cheriton Family Professor and Professor, by courtesy, of Structural Biology and of Molecular & Cellular Physiology

    Current Research and Scholarly InterestsMy lab’s research focuses on computational biology, with an emphasis on 3D molecular structure. We combine two approaches: (1) Bottom-up: given the basic physics governing atomic interactions, use simulations to predict molecular behavior; (2) Top-down: given experimental data, use machine learning to predict molecular structures and properties. We collaborate closely with experimentalists and apply our methods to the discovery of safer, more effective drugs.

  • Eric Dunham

    Eric Dunham

    Professor of Geophysics

    Current Research and Scholarly InterestsPhysics of natural hazards, specifically earthquakes, tsunamis, and volcanoes. Computational geophysics.

  • Jonathan Fan

    Jonathan Fan

    Associate Professor of Electrical Engineering

    Current Research and Scholarly InterestsOptical engineering plays a major role in imaging, communications, energy harvesting, and quantum technologies. We are exploring the next frontier of optical engineering on three fronts. The first is new materials development in the growth of crystalline plasmonic materials and assembly of nanomaterials. The second is novel methods for nanofabrication. The third is new inverse design concepts based on optimization and machine learning.

  • Charbel Farhat

    Charbel Farhat

    Vivian Church Hoff Professor of Aircraft Structures and Professor of Aeronautics and Astronautics

    Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and high-performance software for the design, analysis, and digital twinning of complex systems in aerospace, marine, mechanical, and naval engineering. They contribute major advances to Simulation-Based Engineering Science. Current engineering foci in research are on reliable autonomous carrier landing in rough seas; dissipation of vertical landing energies through structural flexibility; nonlinear aeroelasticity of N+3 aircraft with High Aspect Ratio (HAR) wings; pulsation and flutter of a parachute; pendulum motion in main parachute clusters; coupled fluid-structure interaction (FSI) in supersonic inflatable aerodynamic decelerators for Mars landing; flight dynamics of hypersonic systems and their trajectories; and advanced digital twinning. Current theoretical and computational emphases in research are on high-performance, multi-scale modeling for the high-fidelity analysis of multi-component, multi-physics problems; discrete-event-free embedded boundary methods for CFD and FSI; efficient Bayesian optimization using physics-based surrogate models; modeling and quantifying model-form uncertainty; probabilistic, physics-based machine learning; mechanics-informed artificial neural networks for data-driven constitutive modeling; and efficient nonlinear projection-based model order reduction for time-critical applications such as design, active control, and digital twinning.

  • Ron Fedkiw

    Ron Fedkiw

    Canon Professor in the School of Engineering

    BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.

  • Emily Fox

    Emily Fox

    Professor of Statistics and of Computer Science

    BioEmily Fox is a Professor in the Departments of Statistics and Computer Science at Stanford University. Prior to Stanford, she was the Amazon Professor of Machine Learning in the Paul G. Allen School of Computer Science & Engineering and Department of Statistics at the University of Washington. From 2018-2021, Emily led the Health AI team at Apple, where she was a Distinguished Engineer. Before joining UW, Emily was an Assistant Professor at the Wharton School Department of Statistics at the University of Pennsylvania. She earned her doctorate from Electrical Engineering and Computer Science (EECS) at MIT where her thesis was recognized with EECS' Jin-Au Kong Outstanding Doctoral Thesis Prize and the Leonard J. Savage Award for Best Thesis in Applied Methodology.

    Emily has been awarded a CZ Biohub Investigator Award, Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship, ONR Young Investigator Award, and NSF CAREER Award. Her research interests are in modeling complex time series arising in health, particularly from health wearables and neuroimaging modalities.

  • Oliver Fringer

    Oliver Fringer

    Professor of Civil and Environmental Engineering and of Oceans

    BioFringer's research focuses on the development and application of numerical models and high-performance computational techniques to the study of fundamental processes that influence the dynamics of the coastal ocean, rivers, lakes, and estuaries.

  • Margot Gerritsen

    Margot Gerritsen

    Professor of Energy Resources Engineering, Emerita

    Current Research and Scholarly InterestsResearch
    My work is about understanding and simulating complicated fluid flow problems. My research focuses on the design of highly accurate and efficient parallel computational methods to predict the performance of enhanced oil recovery methods. I'm particularly interested in gas injection and in-situ combustion processes. These recovery methods are extremely challenging to simulate because of the very strong nonlinearities in the governing equations. Outside petroleum engineering, I'm active in coastal ocean simulation with colleagues from the Department of Civil and Environmental Engineering, yacht research and pterosaur flight mechanics with colleagues from the Department of Mechanical and Aeronautical Engineering, and the design of search algorithms in collaboration with the Library of Congress and colleagues from the Institute of Computational and Mathematical Engineering.

    Teaching
    I teach courses in both energy related topics (reservoir simulation, energy, and the environment) in my department, and mathematics for engineers through the Institute of Computational and Mathematical Engineering (ICME). I also initiated two courses in professional development in our department (presentation skills and teaching assistant training), and a consulting course for graduate students in ICME, which offers expertise in computational methods to the Stanford community and selected industries.

    Professional Activities
    Senior Associate Dean, School of Earth, Energy and Environmental Sciences, Stanford (from 2015); Director, Institute for Computational and Mathematical Engineering, Stanford (from 2010); Stanford Fellow (2010-2012); Magne Espedal Professor II, Bergen University (2011-2014); Aldo Leopold Fellow (2009); Chair, SIAM Activity group in Geosciences (2007, present, reelected in 2009); Faculty Research Fellow, Clayman Institute (2008); Elected to Council of Society of Industrial and Applied Mathematics (SIAM) (2007); organizing committee, 2008 Gordon Conference on Flow in Porous Media; producer, Smart Energy podcast channel; Director, Stanford Yacht Research; Co-director and founder, Stanford Center of Excellence for Computational Algorithms in Digital Stewardship; Editor, Journal of Small Craft Technology; Associate editor, Transport in Porous Media; Reviewer for various journals and organizations including SPE, DoE, NSF, Journal of Computational Physics, Journal of Scientific Computing, Transport in Porous Media, Computational Geosciences; member, SIAM, SPE, KIVI, AGU, and APS

  • Kay Giesecke

    Kay Giesecke

    Professor of Management Science and Engineering

    Current Research and Scholarly InterestsKay is a financial technologist whose research agenda is driven by significant applied problems in areas such as investment management, risk analytics, lending, and regulation, where data streams are increasingly large-scale and dynamical, and where computational demands are critical. He develops and analyzes statistical machine learning methods to make explainable data-driven decisions in these and other areas and efficient numerical algorithms to address the associated computational issues.

  • Peter Glynn

    Peter Glynn

    Thomas W. Ford Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsStochastic modeling; statistics; simulation; finance

  • Ashish Goel

    Ashish Goel

    Professor of Management Science and Engineering and, by courtesy, of Computer Science

    BioAshish Goel is a Professor of Management Science and Engineering and (by courtesy) Computer Science at Stanford University. He received his PhD in Computer Science from Stanford in 1999, and was an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002. His research interests lie in the design, analysis, and applications of algorithms.

  • Andrea Goldsmith

    Andrea Goldsmith

    Stephen Harris Professor in the School of Engineering, Emerita

    BioAndrea Goldsmith is the Dean of Engineering and Applied Science and the Arthur LeGrand Doty Professor of Electrical and Computer Engineering at Princeton University. She was previously the Stephen Harris Professor of Engineering and Professor of Electrical Engineering at Stanford University, where she is now Harris Professor Emerita. Her research interests are in information theory, communication theory, and signal processing, and their application to wireless communications, interconnected systems, and biomedical devices. She founded and served as Chief Technical Officer of Plume WiFi (formerly Accelera, Inc.) and of Quantenna (QTNA), Inc, and she serves on the Board of Directors for Intel (INTC), Medtronic (MDT), Crown Castle Inc (CCI), and the Marconi Society. She also serves on the Presidential Council of Advisors on Science and Technology (PCAST). Dr. Goldsmith is a member of the National Academy of Engineering, the Royal Academy of Engineering, and the American Academy of Arts and Sciences. She is a Fellow of the IEEE and has received several awards for her work, including the Marconi Prize, the ACM Sigmobile Outstanding Contribution Award, the IEEE Sumner Technical Field Award, the ACM Athena Lecturer Award, the ComSoc Armstrong Technical Achievement Award, the Kirchmayer Graduate Teaching Award, the WICE Mentoring Award, and the Silicon Valley/San Jose Business Journal’s Women of Influence Award. She is author of the book ``Wireless Communications'' and co-author of the books ``MIMO Wireless Communications,” “Principles of Cognitive Radio,” and “Machine Learning and Wireless Communications,” all published by Cambridge University Press, as well as an inventor on 29 patents. She received the B.S., M.S. and Ph.D. degrees in Electrical Engineering from U.C. Berkeley.

    Dr. Goldsmith is the founding Chair of the IEEE Board of Directors Committee on Diversity and Inclusion. She served as President of the IEEE Information Theory Society in 2009, as founding Chair of its Student Committee, and as founding Editor-in-Chief of the IEEE Journal on Selected Areas in Information Theory. She has also served on the Board of Governors for both the IEEE Information Theory and Communications Societies. At Stanford she served as Chair of Stanford’s Faculty Senate and for multiple terms as a Senator, and on its Academic Council Advisory Board, Budget Group, Committee on Research, Planning and Policy Board, Commissions on Graduate and on Undergraduate Education, Faculty Women’s Forum Steering Committee, and Task Force on Women and Leadership.

  • Kenneth Goodson

    Kenneth Goodson

    Senior Associate Dean for Faculty and Academic Affairs, Davies Family Provostial Professor, and Professor, by courtesy, of Materials Science and Engineering

    Current Research and Scholarly InterestsProf. Goodson’s Nanoheat Lab studies heat transfer in electronic nanostructures, microfluidic heat sinks, and packaging, focussing on basic transport physics and practical impact for industry. We work closely with companies on novel cooling and packaging strategies for power devices, portables, ASICs, & data centers. At present, sponsors and collaborators include ARPA-E, the NSF POETS Center, SRC ASCENT, Google, Intel, Toyota, Ford, among others.

  • Catherine Gorle

    Catherine Gorle

    Associate Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering

    Current Research and Scholarly InterestsGorle's research focuses on the development of predictive flow simulations to support the design of sustainable buildings and cities. Specific topics of interest are the coupling of large- and small-scale models and experiments to quantify uncertainties related to the variability of boundary conditions, the development of uncertainty quantification methods for low-fidelity models using high-fidelity data, and the use of field measurements to validate and improve computational predictions.

  • Leonidas Guibas

    Leonidas Guibas

    Paul Pigott Professor of Engineering and Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsGeometric and topological data analysis and machine learning. Algorithms for the joint analysis of collections of images, 3D models, or trajectories. 3D reconstruction.

  • Pat Hanrahan

    Pat Hanrahan

    Canon Professor in the School of Engineering and Professor of Electrical Engineering, Emeritus

    BioProfessor Hanrahan's current research involves rendering algorithms, high performance graphics architectures, and systems support for graphical interaction. He also has worked on raster graphics systems, computer animation and modeling and scientific visualization, in particular, volume rendering.

  • Kari Hanson

    Kari Hanson

    Lecturer

    BioKari is a former technology executive with a passion for entrepreneurship, innovation, business strategy and making the world a better place. Having worked as a coach, investor, advisor, board member and CFO, she enjoys empowering students and entrepreneurs to thrive in life, the classroom and the marketplace.

  • James Harris

    James Harris

    James and Elenor Chesebrough Professor in the School of Engineering, Emeritus

    BioHarris utilizes molecular beam epitaxy (MBE) of III-V compound semiconductor materials to investigate new materials for electronic and optoelectronic devices. He utilizes heterojunctions, superlattices, quantum wells, and three-dimensional self-assembled quantum dots to create metastable engineered materials with novel or improved properties for electronic and optoelectronic devices. His early work in the 1970's demonstrating a practical heterojunction bipolar transistor led to their application in every mobile phone today and record setting solar cell efficiency. He has recently focused on three areas: 1) integration of photonic devices and micro optics for creation of new minimally invasive bio and medical systems for micro-array and neural imaging and 2) application of nanostructures semiconductors for the acceleration of electrons using light, a dielectric Laser Accelerator (DLA), and 3) novel materials and nano structuring for high efficiency solar cells and photo electrochemical water splitting for the generation of hydrogen.

  • Jerry Harris

    Jerry Harris

    The Cecil H. and Ida M. Green Professor in Geophysics, Emeritus

    Current Research and Scholarly InterestsBiographical Information
    Jerry M. Harris is the Cecil and Ida Green Professor of Geophysics and Associate Dean for the Office of Multicultural Affairs. He joined Stanford in 1988 following 11 years in private industry. He served five years as Geophysics department chair, was the Founding Director of the Stanford Center for Computational Earth and Environmental Science (CEES), and co-launched Stanford's Global Climate and Energy Project (GCEP). Graduates from Jerry's research group, the Stanford Wave Physics Lab, work in private industry, government labs, and universities.

    Research
    My research interests address the physics and dynamics of seismic and electromagnetic waves in complex media. My approach to these problems includes theory, numerical simulation, laboratory methods, and the analysis of field data. My group, collectively known as the Stanford Wave Physics Laboratory, specializes on high frequency borehole methods and low frequency labratory methods. We apply this research to the characterization and monitoring of petroleum and CO2 storage reservoirs.

    Teaching
    I teach courses on waves phenomena for borehole geophysics and tomography. I recently introduced and co-taught a new course on computational geosciences.

    Professional Activities
    I was the First Vice President of the Society of Exploration Geophysicists in 2003-04, and have served as the Distinguished Lecturer for the SPE, SEG, and AAPG.

  • Trevor Hastie

    Trevor Hastie

    John A. Overdeck Professor, Professor of Statistics and of Biomedical Data Sciences
    On Partial Leave from 01/01/2024 To 03/31/2024

    Current Research and Scholarly InterestsFlexible statistical modeling for prediction and representation of data arising in biology, medicine, science or industry. Statistical and machine learning tools have gained importance over the years. Part of Hastie's work has been to bridge the gap between traditional statistical methodology and the achievements made in machine learning.

  • Mark Holodniy

    Mark Holodniy

    Professor of Medicine (Infectious Diseases)

    Current Research and Scholarly InterestsMy research program is currently focused in three areas: 1) Translational research (viral evolution and antiviral resistance prevalence and development), 2) Clinical trials (diagnostic assay/medical device, antimicrobials and immunomodulators), and 3) Health services research focusing on public health, infectious diseases and clinical outcomes.

  • Mark Horowitz

    Mark Horowitz

    Fortinet Founders Chair of the Department of Electrical Engineering , Yahoo! Founders Professor in the School of Engineering and Professor of Computer Science

    BioProfessor Horowitz initially focused on designing high-performance digital systems by combining work in computer-aided design tools, circuit design, and system architecture. During this time, he built a number of early RISC microprocessors, and contributed to the design of early distributed shared memory multiprocessors. In 1990, Dr. Horowitz took leave from Stanford to help start Rambus Inc., a company designing high-bandwidth memory interface technology. After returning in 1991, his research group pioneered many innovations in high-speed link design, and many of today’s high speed link designs are designed by his former students or colleagues from Rambus.

    In the 2000s he started a long collaboration with Prof. Levoy on computational photography, which included work that led to the Lytro camera, whose photographs could be refocused after they were captured.. Dr. Horowitz's current research interests are quite broad and span using EE and CS analysis methods to problems in neuro and molecular biology to creating new agile design methodologies for analog and digital VLSI circuits. He remains interested in learning new things, and building interdisciplinary teams.

  • Gianluca Iaccarino

    Gianluca Iaccarino

    Professor of Mechanical Engineering

    Current Research and Scholarly InterestsComputing and data for energy, health and engineering

    Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
    My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.

    Multidisciplinary Teaching

    I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results.

  • Doug James

    Doug James

    Professor of Computer Science and, by courtesy, of Music

    Current Research and Scholarly InterestsComputer graphics & animation, physics-based sound synthesis, computational physics, haptics, reduced-order modeling

  • Antony Jameson

    Antony Jameson

    Professor (Research) of Aeronautics and Astronautics, Emeritus

    BioProfessor Jameson's research focuses on the numerical solution of partial differential equations with applications to subsonic, transonic, and supersonic flow past complex configurations, as well as aerodynamic shape optimization.