School of Engineering
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Alcatel-Lucent Professor in Communications and Networking and Professor of Particle Physics and Astrophysics and of Photon Science
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.
Vance D. and Arlene C. Coffman ProfessorOn Partial Leave from 10/01/2020 To 06/30/2021
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.
Associate Professor of Electrical EngineeringOn Partial Leave from 04/01/2021 To 06/30/2021
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.
Thomas More Storke Professor, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Education
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, a Senior Fellow at the Woods Institute for the Environment, and a Faculty Leader at Stanford’s Center for Longevity. He earned a B.A. cum laude 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.
He has published more than 100 academic papers, in interdisciplinary journals such as Science, the Journal of the American Medical Association, and PLoS One, as well domain-specific journals in the fields of communication, computer science, education, environmental science, law, marketing, medicine, political science, and psychology. His work has been continuously funded by the National Science Foundation for 15 years.
Bailenson consults pro bono on Virtual Reality policy for government agencies including the State Department, the US Senate, Congress, the California Supreme Court, the Federal Communication Committee, the U.S. Army, Navy, and Air Force, the Department of Defense, the Department of Energy, the National Research Council, and the National Institutes of Health.
His first book Infinite Reality, co-authored with Jim Blascovich, was quoted by the U.S. Supreme Court outlining the effects of immersive media. 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, CNN, PBS NewsHour, Wired, National Geographic, Slate, The San Francisco Chronicle, and The Chronicle of Higher Education, and has produced or directed five Virtual Reality documentary experiences which were official selections at the Tribeca Film Festival. His lab’s research has exhibited publicly at museums and aquariums, including a permanent installation at the San Jose Tech Museum.
Barney and Estelle Morris Professor
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.
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.
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)
Samsung Professor in the School of Engineering and Professor, by courtesy, of Computer Science and of Management Science and Engineering
BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is 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.
Professor Boyd 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. He is a Fellow of the IEEE, SIAM, and INFORMS, 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, with citation: “For excellence in classroom teaching, textbook and monograph preparation, and undergraduate and graduate mentoring of students in the area of systems, control, and optimization.” 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
BioLeticia Britos Cavagnaro, Ph.D., is 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 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 nationwide. She is an adjunct professor at the d.school, where she teaches Stanford students of all disciplines how to build their creative confidence to become engines of innovation in teams and organizations. Leticia has 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) at Stanford’s School of Education. Having witnessed the journey of students who are transformed by their experience at the d.school, bringing design thinking to more people beyond Stanford has become a priority for Leticia, and she has worked with hundreds of educators and students of all ages, as well as corporate and non-profit leaders in the US and abroad. In the Summer of 2013, Leticia engaged thousands of people from over 130 countries in learning design thinking and applying the methodology to innovate in their contexts, via an experiential MOOC (http://novoed.com/designthinking).
Find out more about Leticia's work at:
Designing for Change: Using social learning to understand organizational transformation (book about the UIF program): https://www.amazon.com/Designing-Change-understand-organizational-transformation/dp/1733735402/
Connect with Leticia:
Twitter: @LeticiaBritosC (twitter.com/leticiabritosc)
Professor of Biomedical Data Science, of Genetics and, by courtesy, of Biology
Current Research and Scholarly InterestsMy genetics research focuses on analyzing genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine. We focus on novel methods development for complex disease genetics and risk prediction in multi-ethnic settings. I am also interested in clinical data science and development of new diagnostics.I am also interested in disruptive innovation for healthcare including modeling long-term risk shifts and novel payment models.
Barnum-Simons Chair in 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.
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
BioCarissa Carter is the Director of Teaching + Learning 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 offering. She teaches courses on the intersection of data and design, design for climate change, and maps and the visual sorting of information.
Associate Professor of Electrical Engineering and Center Fellow, by courtesy, at the Precourt Institute for Energy
Current Research and Scholarly InterestsWide bandap materials & devices for RF, Power and energy efficient electronics
John M. Cioffi
Hitachi America Professor in the School of Engineering, Emeritus
BioJohn M. Cioffi taught Stanford's graduate electrical engineering course sequence in digital communications for over 20 years from 1986 to 2008, when he retired to emeritus. Cioffi's research interests were in the theory of transmitting the highest possible data rates on a number of different communications channels, many of which efforts were spun out of Stanford through he and/or his many former PhD students to companies, most notably including the basic designed used worldwide on more than 500 million DSL connections. Cioffi also over saw the prototype developments for the worlds first cable modem and digital-audio broadcast system. 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 was co-inventer 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 centered on these areas.
Professor of Mechanical Engineering
Current Research and Scholarly InterestsProfessor Darve's research is focused on the development of numerical methods for high-performance scientific computing, numerical linear algebra, fast algorithms, parallel computing, anomaly detection, and machine learning with applications in engineering.
Anne T. and Robert M. Bass Professor in the School of Humanities and SciencesOn Leave from 10/01/2020 To 06/30/2021
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.
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.
Associate Professor of Computer Science and, by courtesy, of Molecular and Cellular Physiology and of Structural Biology
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.
Associate Professor of Geophysics
Current Research and Scholarly InterestsPhysics of natural hazards, specifically earthquakes, tsunamis, and volcanoes. Computational geophysics.
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.
Vivian Church Hoff Professor of Aircraft Structures, Professor of Mechanical Engineering and Director of the Army High Performance Computing Research Center
Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and high-performance software for the design and analysis 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 the nonlinear aeroelasticity and flight dynamics of Micro Aerial Vehicles (MAVs) with flexible flapping wings and N+3 aircraft with High Aspect Ratio (HAR) wings, layout optimization and additive manufacturing of wing structures, supersonic inflatable aerodynamic decelerators for Mars landing, and the reliable automated carrier landing via model predictive control. Current theoretical and computational emphases in research are on high-performance, multi-scale modeling for the high-fidelity analysis of multi-physics problems, high-order embedded boundary methods, uncertainty quantification, probabilistic machine learning, and efficient projection-based model order reduction as well as other forms of physics-based machine learning for time-critical applications such as design, active control, and digital twins.
Professor of Computer Science
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.
Professor of Civil and Environmental Engineering
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.
Professor of Energy Resources Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Civil and Environmental EngineeringOn Leave from 04/01/2021 To 06/30/2021
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.
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.
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
Professor of Management Science and EngineeringOn Partial Leave from 04/01/2021 To 06/30/2021
Current Research and Scholarly InterestsKay is a financial technologist and engineer. He develops stochastic financial models, designs statistical methods for analyzing financial data, examines simulation and other numerical algorithms for solving the associated computational problems, and performs empirical analyses. Much of Kay's work is driven by important applications in areas such as credit risk management, investment management, and, most recently, housing finance.
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
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.
Stephen Harris Professor in the School of Engineering, Emerita
BioAndrea Goldsmith is the Stephen Harris professor in the School of Engineering and professor of Electrical Engineering at Stanford University. Her research interests are in information theory, communication theory, and signal processing, and their application to wireless communications, interconnected systems, and neuroscience. She co-founded and served as Chief Technical Officer and Board member of Plume WiFi and of Quantenna (QTNA), and she currently serves on the Board of Directors for Medtronic (MDT) and Crown Castle Inc. (CCI). She has also been a member or chair of the technical advisory boards for Quantenna (QTNA), Sequans (SQNS), Interdigital (IDCC) and Cohere. Goldsmith has launched and led several multi-university research projects including DARPA’s ITMANET program, and she is currently a Principle Investigator in the NSF Center on the Science of Information. Prior to Stanford she held positions at Caltech, Maxim Technologies, Memorylink Corporation, and AT&T Bell Laboratories. Dr. Goldsmith is a member of the National Academy of Engineering and the American Academy of Arts and Sciences, a Fellow of the IEEE and of Stanford, and has received several awards for her work, including the IEEE Eric E. Sumner Technical Field Award in Communications Technology, the ComSoc Edwin H. Armstrong Achievement Award as well as Technical Achievement Awards in Communications Theory and in Wireless Communications, the National Academy of Engineering Gilbreth Lecture 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'' and “Principles of Cognitive Radio,” all published by Cambridge University Press, as well as an inventor on 29 patents. She has served in various leadership roles in the IEEE and in industrial groups aimed at diversifying STEM fields, and is currently the founding chair of the IEEE Committee on Diversity, Inclusion, and Professional Ethics. At Stanford she has served as chair and a member of the Faculty Senate and on the Planning and Policy Board, Committee on Research, Commissions on Graduate Education and on Undergraduate Education, Task Force on Women and Leadership, and the Faculty Women's Forum Steering Committee. She currently serves on Stanford's Budget Group, Advisory Board, and in the Faculty Senate.
Davies Family Provostial Professor, Senior Associate Dean for Faculty and Academic Affairs 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.
Assistant Professor of Civil and Environmental 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.
Paul Pigott Professor in the School 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.
Canon USA Professor in the School of Engineering and Professor of Electrical Engineering
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.
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.
Kari is currently designing and co-teaching the ICME Analytics Accelerator, a project based research course for graduate students from multiple disciplines.
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. 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.
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.
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.
I teach courses on waves phenomena for borehole geophysics and tomography. I recently introduced and co-taught a new course on computational geosciences.
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.
John A. Overdeck Professor, Professor of Statistics and of Biomedical Data Sciences
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.
Professor of Medicine (Infectious Diseases) at the Palo Alto Veterans Affairs Health Care System
Current Research and Scholarly InterestsMy research program is currently focused in three areas: 1) Translational research (HCV/HIV 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 cost effectiveness of antiviral utilization and clincal outcomes.
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 computation photography, that included work that led to the Lytro camera. 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.
Professor of Mechanical Engineering and Director, Institute for Computational and Mathematical 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.
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.
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
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.
Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering and of Computer Science
BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).