School of Engineering
Showing 1-100 of 133 Results
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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.
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Maneesh Agrawala
Forest Baskett Professor and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsComputer Graphics, Human Computer Interaction and Visualization.
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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.
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Clark Barrett
Professor (Research) of Computer Science
Current Research and Scholarly InterestsAutomated reasoning; satisfiability modulo theories (SMT); formal methods;
formal verification; verification of smart contracts; verification of neural
networks; AI safety; security; hardware design productivity and verification. -
Gill Bejerano
Professor of Developmental Biology, of Computer Science, of Pediatrics (Genetics) and of Biomedical Data Science
Current Research and Scholarly Interests1. Automating monogenic patient diagnosis.
2. The genomic signatures of independent divergent and convergent trait evolution in mammals.
3. The logic of human gene regulation.
4. The reasons for sequence ultraconservation.
5. Cryptogenomics to bridge medical silos.
6. Cryptogenetics to debate social injustice.
7. Managing patient risk using machine learning.
8. Understanding the flow of money in the US healthcare system. -
Michael Bernstein
Associate Professor of Computer Science
BioMichael Bernstein is an Associate Professor of Computer Science at Stanford University, where he is a Bass University Fellow and STMicroelectronics Faculty Scholar. His research in human-computer interaction focuses on the design of social computing systems. This research has won best paper awards at top conferences in human-computer interaction, including CHI, CSCW, ICWSM, and UIST, and has been reported in venues such as The New York Times, Science, Wired, and The Guardian. Michael has been recognized with an Alfred P. Sloan Fellowship, UIST Lasting Impact Award, and the Patrick J. McGovern Tech for Humanity Prize. He holds a bachelor's degree in Symbolic Systems from Stanford University, as well as a master's degree and a Ph.D. in Computer Science from MIT.
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Jeannette Bohg
Assistant Professor of Computer Science
BioJeannette Bohg is an Assistant Professor of Computer Science at Stanford University. She was a group leader at the Autonomous Motion Department (AMD) of the MPI for Intelligent Systems until September 2017. Before joining AMD in January 2012, Jeannette Bohg was a PhD student at the Division of Robotics, Perception and Learning (RPL) at KTH in Stockholm. In her thesis, she proposed novel methods towards multi-modal scene understanding for robotic grasping. She also studied at Chalmers in Gothenburg and at the Technical University in Dresden where she received her Master in Art and Technology and her Diploma in Computer Science, respectively. Her research focuses on perception and learning for autonomous robotic manipulation and grasping. She is specifically interesting in developing methods that are goal-directed, real-time and multi-modal such that they can provide meaningful feedback for execution and learning. Jeannette Bohg has received several awards, most notably the 2019 IEEE International Conference on Robotics and Automation (ICRA) Best Paper Award, the 2019 IEEE Robotics and Automation Society Early Career Award and the 2017 IEEE Robotics and Automation Letters (RA-L) Best Paper Award.
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Dan Boneh
Cryptography Professor, Professor of Electrical Engineering and Senior Fellow at the Freeman Spogli Institute for International Studies
BioProfessor Boneh heads the applied cryptography group and co-direct the computer security lab. Professor Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, web security, security for mobile devices, and cryptanalysis. He is the author of over a hundred publications in the field and is a Packard and Alfred P. Sloan fellow. He is a recipient of the 2014 ACM prize and the 2013 Godel prize. In 2011 Dr. Boneh received the Ishii award for industry education innovation. Professor Boneh received his Ph.D from Princeton University and joined Stanford in 1997.
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Adam Bouland
Assistant Professor of Computer Science
BioAdam Bouland is an Assistant Professor of Computer Science. His research focuses on quantum computing theory and connections between computational complexity and physics. Please see http://theory.stanford.edu/~abouland/ for details.
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Karl David Broman
Visiting Professor, Computer Science
BioDavid Broman is currently a Visiting Professor at the Computer Science Department at Stanford University. He is a Professor at the Department of Computer Science, KTH Royal Institute of Technology in Stockholm, Sweden. His research focuses on the intersection of (i) programming languages and compilers, (ii) real-time and cyber-physical systems, and (iii) probabilistic machine learning.
For further information, please see the web link at the top of the page (next to my name). -
Moses Charikar
Donald E. Knuth Professor and Professor, by courtesy, of Mathematics
Current Research and Scholarly InterestsEfficient algorithmic techniques for processing, searching and indexing massive high-dimensional data sets; efficient algorithms for computational problems in high-dimensional statistics and optimization problems in machine learning; approximation algorithms for discrete optimization problems with provable guarantees; convex optimization approaches for non-convex combinatorial optimization problems; low-distortion embeddings of finite metric spaces.
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Dora Demszky
Assistant Professor of Education and, by courtesy, of Computer Science
BioDr. Demszky is an Assistant Professor in Education Data Science at the Graduate School of Education at Stanford University. She works on developing natural language processing methods to support equitable and student-centered instruction. She has developed tools to give feedback to teachers on dialogic instructional practices, to analyze representation in textbooks, measure the presence of dialect features in text, among others. Dr Demszky has received her PhD in Linguistics at Stanford University, supervised by Dr Dan Jurafsky. Prior to her PhD, Dr. Demszky received a BA summa cum laude from Princeton University in Linguistics with a minor in Computer Science.
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David Dill
Donald E. Knuth Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsSecure and reliable blockchain technology at Facebook.
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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.
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John Duchi
Associate Professor of Statistics, of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy work spans statistical learning, optimization, information theory, and computation, with a few driving goals: 1. To discover statistical learning procedures that optimally trade between real-world resources while maintaining statistical efficiency. 2. To build efficient large-scale optimization methods that move beyond bespoke solutions to methods that robustly work. 3. To develop tools to assess and guarantee the validity of---and confidence we should have in---machine-learned systems.
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Zakir Durumeric
Assistant Professor of Computer Science
BioI am an Assistant Professor of Computer Science. My research brings a large-scale, empirical approach to the study of security, abuse, and misinformation on the Internet. I build systems to measure complex networked ecosystems, and I use the resulting perspective to understand real-world behavior, uncover weaknesses and attacks, architect more resilient approaches, and guide policy decisions.
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Dawson Engler
Associate Professor of Computer Science and of Electrical Engineering
BioEngler's research focuses both on building interesting software systems and on discovering and exploring the underlying principles of all systems.
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Stefano Ermon
Associate Professor of Computer Science and Senior Fellow at the Woods Institute for the Environment
BioI am an Assistant Professor in the Department of Computer Science at Stanford University, where I am affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.
My research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. -
Kayvon Fatahalian
Associate Professor of Computer Science
BioKayvon Fatahalian is an Associate Professor in the Computer Science Department at Stanford University. Kayvon's research focuses on the design of systems for real-time graphics, high-efficiency simulation engines for applications in entertainment and AI, and platforms for the analysis of images and videos at scale.
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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.
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Bruno Felisberto Martins Ribeiro
Visiting Associate Professor, Computer Science
BioBruno Ribeiro is an Associate Professor in the Department of Computer Science at Purdue University and currently a Visiting Associate Professor at Stanford University. Before joining Purdue, he earned his Ph.D. from the University of Massachusetts Amherst and was a postdoctoral fellow at Carnegie Mellon University. Ribeiro has made significant contributions in the intersection between invariant theory, graph learning, and out-of-distribution robustness. Ribeiro received an NSF CAREER award in 2020, an Amazon Research Award in 2022, and multiple best paper awards.
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Richard Fikes
Professor (Research) of Computer Science, Emeritus
BioRichard Fikes has a long and distinguished record as an innovative leader in the development of techniques for effectively representing and using knowledge in computer systems. He is best known as co-developer of the STRIPS automatic planning system, KIF (Knowledge Interchange Format), the Ontolingua ontology representation language and Web-based ontology development environment, the OKBC (Open Knowledge Base Connectivity) API for knowledge servers, and IntelliCorp's KEE system. At Stanford, he led projects focused on developing large-scale distributed repositories of computer-interpretable knowledge, collaborative development of multi-use ontologies, enabling technology for the Semantic Web, reasoning methods applicable to large-scale knowledge bases, and knowledge-based technology for intelligence analysts. He was principal investigator of major projects for multiple Federal Government agencies including the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Community’s Advanced Research and Development Activity (ARDA).
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Chelsea Finn
Assistant Professor of Computer Science and of Electrical Engineering
On Partial Leave from 04/01/2024 To 06/30/2024BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, an NSF graduate fellowship, a Facebook fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.
Website: https://ai.stanford.edu/~cbfinn -
Sean Follmer
Associate Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsHuman Computer Interaction, Haptics, Robotics, Human Centered Design
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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. -
Michael Genesereth
Associate Professor of Computer Science and, by courtesy, of Law
BioGenesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Computational Law, and General Game Playing. He is one of the founders of Teknowledge, CommerceNet, Mergent Systems, and Symbium. Genesereth is the director of the Logic Group at Stanford and the founder and research director of CodeX - the Stanford Center for Legal Informatics.
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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.
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Christopher Gregg
Associate Professor (Teaching) of Computer Science
BioChris Gregg received his Ph.D. in Computer Engineering from the University of Virginia in 2012, has a Master's of Education from Harvard University (2002), and a BS in Electrical Engineering from Johns Hopkins University (1994). Prior to becoming a lecturer at Stanford, Chris was a lecturer in the computer science department at Tufts University, and prior to that he taught high school physics in Massachusetts and California for seven years. Chris was on active duty in the Navy for seven years, and remains as a Commander in the Navy Reserves in the Information Warfare / Cryptology community.
Chris's research interests include computer architecture (specifically, general purpose computing on GPUs) and the pedagogy of computer science teaching and instruction. -
Carlos Ernesto Guestrin
Professor of Computer Science
BioCarlos Guestrin is a Professor in the Computer Science Department at Stanford University. His previous positions include the Amazon Professor of Machine Learning at the Computer Science & Engineering Department of the University of Washington, the Finmeccanica Associate Professor at Carnegie Mellon University, and the Senior Director of Machine Learning and AI at Apple, after the acquisition of Turi, Inc. (formerly GraphLab and Dato) — Carlos co-founded Turi, which developed a platform for developers and data scientist to build and deploy intelligent applications. He is a technical advisor for OctoML.ai. His team also released a number of popular open-source projects, including XGBoost, LIME, Apache TVM, MXNet, Turi Create, GraphLab/PowerGraph, SFrame, and GraphChi.
Carlos received the IJCAI Computers and Thought Award and the Presidential Early Career Award for Scientists and Engineers (PECASE). He is also a recipient of the ONR Young Investigator Award, NSF Career Award, Alfred P. Sloan Fellowship, and IBM Faculty Fellowship, and was named one of the 2008 ‘Brilliant 10’ by Popular Science Magazine. Carlos’ work received awards at a number of conferences and journals, including ACL, AISTATS, ICML, IPSN, JAIR, JWRPM, KDD, NeurIPS, UAI, and VLDB. He is a former member of the Information Sciences and Technology (ISAT) advisory group for DARPA. -
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.
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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.
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John Hennessy
President Emeritus, Shriram Family Director of the Knight-Hennessy Scholars Program, James F. and Mary Lynn Gibbons Professor and Professor of Electrical Engineering and of Computer Science
BioJohn L. Hennessy joined Stanford’s faculty in 1977 as an assistant professor of electrical engineering. He rose through the academic ranks to full professorship in 1986 and was the inaugural Willard R. and Inez Kerr Bell Professor of Electrical Engineering and Computer Science from 1987 to 2004.
From 1983 to 1993, Dr. Hennessy was director of the Computer Systems Laboratory, a research and teaching center operated by the Departments of Electrical Engineering and Computer Science that fosters research in computer systems design. He served as chair of computer science from 1994 to 1996 and, in 1996, was named dean of the School of Engineering. As dean, he launched a five-year plan that laid the groundwork for new activities in bioengineering and biomedical engineering. In 1999, he was named provost, the university’s chief academic and financial officer. As provost, he continued his efforts to foster interdisciplinary activities in the biosciences and bioengineering and oversaw improvements in faculty and staff compensation. In October 2000, he was inaugurated as Stanford University’s 10th president, a position he held until 2016. In 2016, he cofounded the Knight-Hennessy Scholars Program, which provides scholarships and leadership development for a global community of scholars enrolled in graduate programs at Stanford. The program admitted it's first class in 2018 and will provide full scholarships for up to 100 100 students every year.
A pioneer in computer architecture, in 1981 Dr. Hennessy drew together researchers to focus on a computer architecture known as RISC (Reduced Instruction Set Computer), a technology that has revolutionized the computer industry by increasing performance while reducing costs. In addition to his role in the basic research, Dr. Hennessy helped transfer this technology to industry. In 1984, he cofounded MIPS Computer Systems, now MIPS Technologies, which designs microprocessors. In recent years, his research has focused on the architecture of high-performance computers.
Dr. Hennessy is a recipient of the 2000 IEEE John von Neumann Medal, the 2000 ASEE Benjamin Garver Lamme Award, the 2001 ACM Eckert-Mauchly Award, the 2001 Seymour Cray Computer Engineering Award, a 2004 NEC C&C Prize for lifetime achievement in computer science and engineering, a 2005 Founders Award from the American Academy of Arts and Sciences and the 2012 IEEE Medal of Honor, IEEE's highest award. He is a member of the National Academy of Engineering and the National Academy of Sciences, and he is a fellow of the American Academy of Arts and Sciences, the Association for Computing Machinery, and the Institute of Electrical and Electronics Engineers.
He has lectured and published widely and is the co-author of two internationally used undergraduate and graduate textbooks on computer architecture design. Dr. Hennessy earned his bachelor’s degree in electrical engineering from Villanova University and his master’s and doctoral degrees in computer science from the State University of New York at Stony Brook. -
Daniel Ho
William Benjamin Scott & Luna M. Scott Professor of Law, Professor of Political Science, Senior Fellow at the Stanford Institute for Economic Policy Research, at the Stanford Institute for HAI and Professor, by courtesy, of Computer Science
BioDaniel E. Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, Professor of Computer Science (by courtesy), Senior Fellow at Stanford's Institute for Human-Centered Artificial Intelligence, and Senior Fellow at the Stanford Institute for Economic Policy Research at Stanford University. He is a Faculty Fellow at the Center for Advanced Study in the Behavioral Sciences and is Director of the Regulation, Evaluation, and Governance Lab (RegLab). Ho serves on the National Artificial Intelligence Advisory Commission (NAIAC), advising the White House on artificial intelligence, as Senior Advisor on Responsible AI at the U.S. Department of Labor, and as a Public Member of the Administrative Conference of the United States (ACUS). He received his J.D. from Yale Law School and Ph.D. from Harvard University and clerked for Judge Stephen F. Williams on the U.S. Court of Appeals, District of Columbia Circuit.
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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. -
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
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Zerina Kapetanovic
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science and of Geophysics
BioZerina Kapetanovic is an Assistant Professor in the Department of Electrical Engineering at Stanford University working in the area of low-power wireless communication, sensing, and Internet of Things (IoT) systems. Prior to starting at Stanford, Kapetanovic was a postdoctoral researcher at Microsoft Research in the Networking Research Group and Research for Industry Group.
Kapetanovic's research has been recognized by the Yang Research Award, the Distinguished Dissertation Award from the University of Washington, and is a Terman Faculty Fellow. She also received the Microsoft Research Distinguished Dissertation Grant and was selected to attend the 2020 UC Berkeley Rising Stars in EECS Workshop. Kapetanovic completed her PhD in Electrical Engineering from the University of Washington in 2022. -
Monroe Kennedy III
Assistant Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy research focus is to develop technology that improves everyday life by anticipating and acting on the needs of human counterparts. My research can be divided into the following sub-categories: robotic assistants, connected devices and intelligent wearables. My Assistive Robotics and Manipulation lab focuses heavily on both the analytical and experimental components of assistive technology design.
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Oussama Khatib
Weichai Professor and Professor, by courtesy, of Electrical Engineering
BioRobotics research on novel control architectures, algorithms, sensing, and human-friendly designs for advanced capabilities in complex environments. With a focus on enabling robots to interact cooperatively and safely with humans and the physical world, these studies bring understanding of human movements for therapy, athletic training, and performance enhancement. Our work on understanding human cognitive task representation and physical skills is enabling transfer for increased robot autonomy. With these core capabilities, we are exploring applications in healthcare and wellness, industry and service, farms and smart cities, and dangerous and unreachable settings -- deep in oceans, mines, and space.
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Fredrik Kjolstad
Assistant Professor of Computer Science
BioFredrik Kjolstad is an Assistant Professor in Computer Science at Stanford University. He works on topics in compilers, programming models, and systems, with an emphasis on compilers for sparse computing problems where we need to separate the algorithms from data representation, as well as fast compilers. He has received the NSF CAREER Award, the MIT EECS First Place George M. Sprowls PhD Thesis Award in Computer Science, the Rosing Award, an Adobe Fellowship, a Google Research Scholarship, and several best/distinguished paper awards.
Website: https://fredrikbk.com/ -
Donald Knuth
Fletcher Jones Professor of Computer Science, Emeritus
BioDonald Ervin Knuth is an American computer scientist, mathematician, and Professor Emeritus at Stanford University.
He is the author of the multi-volume work The Art of Computer Programming and has been called the "father" of the analysis of algorithms. He contributed to the development of the rigorous analysis of the computational complexity of algorithms and systematized formal mathematical techniques for it. In the process he also popularized the asymptotic notation. In addition to fundamental contributions in several branches of theoretical computer science, Knuth is the creator of the TeX computer typesetting system, the related METAFONT font definition language and rendering system, and the Computer Modern family of typefaces.
As a writer and scholar,[4] Knuth created the WEB and CWEB computer programming systems designed to encourage and facilitate literate programming, and designed the MIX/MMIX instruction set architectures. As a member of the academic and scientific community, Knuth is strongly opposed to the policy of granting software patents. He has expressed his disagreement directly to the patent offices of the United States and Europe. (via Wikipedia) -
Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Computer Science
BioMykel Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is an author of "Decision Making under Uncertainty: Theory and Application" (2015), "Algorithms for Optimization" (2019), and "Algorithms for Decision Making" (2022), all from MIT Press. He is a third generation pilot.
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Christoforos Kozyrakis
Professor of Electrical Engineering and of Computer Science
BioChristos Kozyrakis is a Professor of Electrical Engineering and Computer Science at Stanford University. His primary research areas are computer architecture and computer systems. His current work focuses on cloud computing, systems for machine learning, and machine learning for systems. Christos leads the MAST research group. He is also the faculty director of the Stanford Platform Lab.
Christos holds a BS degree from the University of Crete and a PhD degree from the University of California at Berkeley. He is a fellow of the ACM and the IEEE. He has received the ACM SIGARCH Maurice Wilkes Award, the ISCA Influential Paper Award, the NSF Career Award, the Okawa Foundation Research Grant, and faculty awards by IBM, Microsoft, and Google. -
Anshul Kundaje
Associate Professor of Genetics
Current Research and Scholarly InterestsWe develop statistical and machine learning frameworks to learn predictive, dynamic and causal models of gene regulation from heterogeneous functional genomics data.
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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford Open Virtual Assistant Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.
Professor Lam's current research is on conversational virtual assistants with an emphasis on privacy protection. Her research uses deep learning to map task-oriented natural language dialogues into formal semantics, represented by a new executable programming language called ThingTalk. Her Almond virtual assistant, trained on open knowledge graphs and IoT API standards, can be easily customized to perform new tasks. She is leading an Open Virtual Assistant Initiative to create the largest, open, crowdsourced language semantics model to promote open access in all languages. Her decentralized Almond virtual assistant that supports fine-grain sharing with privacy has received Popular Science's Best of What's New Award in Security in 2019.
Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”. She was on the founding team of Tensilica, now a part of Cadence.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow. -
James Landay
Denning Co-Director (Acting) of Stanford HAI, Anand Rajaraman and Venky Harinarayan Professor and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsLanday's current research interests include Technology to Support Behavior Change (especially for health and sustainability), Demonstrational User Interfaces, Mobile & Ubiquitous Computing, Cross-Cultural Interface Design, Human-Centered AI, and User Interface Design Tools. He has developed tools, techniques, and a top professional book on Web Interface Design.
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Cynthia Bailey (Lee)
Senior Lecturer of Computer Science
Current Research and Scholarly InterestsI have a PhD in Computer Science from the University of California, San Diego, in the area of High-Performance Computing (HPC), specifically market-based scheduling algorithms. My graduate research was done as part of San Diego Supercomputer Center (SDSC)'s Performance Modeling and Characterization Lab (PMaC), where I investigated economic models of scheduling on high performance computing systems. My adviser was Allan Snavely of SDSC.
My dissertation abstract is as follows: Effective management of Grid and HPC resources is essential to maximizing return on the substantial infrastructure investment these resources entail. An important prerequisite to effective resource management is productive interaction between the user and scheduler. My work analyzes several aspects of the user-scheduler relationship and develops solutions to three of the most vexing barriers between the two. First, users' monetary valuation of compute time and schedule turnaround time is examined in terms of a utility function. Second, responsiveness of the scheduler to users' varied valuations is optimized via a genetic algorithm heuristic, creating a controlled market for computation. Finally, the chronic problem of inaccurate user runtime requests, and its implications for scheduler performance, is examined, along with mitigation techniques.
My current research projects are in the area of Computer Science Education, with an emphasis on assessment and the use of Peer Instruction pedagogy in lecture. With colleagues Mark Guzdial, Leo Porter, and Beth Simon, I run the New CS Faculty Teaching Workshop, an annual "bootcamp" on how to teach effectively that draws attendees from dozens of the top CS programs in the country. The short-term goal is to give newly-hired faculty entering their first year of teaching the skills they need to succeed for themselves and their students. The long-term goal is to transform undergraduate education in CS by seeding our best rising stars with best practices so they can create communities of practice as their institutions and mentor their students in active learning strategies, creating a culture where these are the new norm. -
Jure Leskovec
Professor of Computer Science
BioJure Leskovec is Professor of Computer Science at Stanford University. He is affiliated with the Stanford AI Lab, Machine Learning Group and the Center for Research on Foundation Models. In the past, he served as a Chief Scientist at Pinterest and was an investigator at Chan Zuckerberg BioHub. Leskovec recently pioneered the field of Graph Neural Networks and co-authored PyG, the most widely-used graph neural network library. Research from his group has been used by many countries to fight COVID-19 pandemic, and has been incorporated into products at Facebook, Pinterest, Uber, YouTube, Amazon, and more.
His research received several awards including Microsoft Research Faculty Fellowship in 2011, Okawa Research award in 2012, Alfred P. Sloan Fellowship in 2012, Lagrange Prize in 2015, and ICDM Research Contributions Award in 2019. His research contributions have spanned social networks, data mining and machine learning, and computational biomedicine with the focus on drug discovery. His work has won 12 best paper awards and 5 10-year test of time awards at a premier venues in these research areas.
Leskovec received his bachelor's degree in computer science from University of Ljubljana, Slovenia, PhD in machine learning from Carnegie Mellon University and postdoctoral training at Cornell University. -
Philip Levis
Professor of Computer Science and of Electrical Engineering
BioProfessor Levis' research focuses on the design and implementation of efficient software systems for embedded wireless sensor networks; embedded network sensor architecture and design; systems programming and software engineering.
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Marc Levoy
VMware Founders Professor in Computer Science and Professor of Electrical Engineering, Emeritus
BioLevoy's current interests include the science and art of photography, computational photography, light field sensing and display, and applications of computer graphics in microscopy and biology.
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Fei-Fei Li
Sequoia Capital Professor, Denning Co-Director (On Leave) of Stanford HAI, Senior Fellow at HAI and Professor, by courtesy, of Operations, Information and Technology at the Graduate School of Business
On Partial Leave from 01/01/2024 To 12/31/2025Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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Percy Liang
Associate Professor of Computer Science, Senior Fellow at the Stanford Institute for HAI, and Associate Professor, by courtesy, of Statistics
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).
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Scott W Linderman
Assistant Professor of Statistics and, by courtesy, of Computer Science and of Electrical Engineering
BioScott is an Assistant Professor of Statistics and, by courtesy, Electrical Engineering and Computer Science at Stanford University. He is also an Institute Scholar in the Wu Tsai Neurosciences Institute and a member of Stanford Bio-X and the Stanford AI Lab. His lab works at the intersection of machine learning and computational neuroscience, developing statistical methods to analyze large scale neural data. Previously, Scott was a postdoctoral fellow with Liam Paninski and David Blei at Columbia University, and he completed his PhD in Computer Science at Harvard University with Ryan Adams and Leslie Valiant. He obtained his undergraduate degree in Electrical and Computer Engineering from Cornell University and spent three years as a software engineer at Microsoft before graduate school.
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C. Karen Liu
Professor of Computer Science
BioC. Karen Liu is a professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. Liu's research interests are in computer graphics and robotics, including physics-based animation, character animation, optimal control, reinforcement learning, and computational biomechanics. She developed computational approaches to modeling realistic and natural human movements, learning complex control policies for humanoids and assistive robots, and advancing fundamental numerical simulation and optimal control algorithms. The algorithms and software developed in her lab have fostered interdisciplinary collaboration with researchers in robotics, computer graphics, mechanical engineering, biomechanics, neuroscience, and biology. Liu received a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and was named Young Innovators Under 35 by Technology Review. In 2012, Liu received the ACM SIGGRAPH Significant New Researcher Award for her contribution in the field of computer graphics.
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Christopher Manning
Thomas M. Siebel Professor of Machine Learning, Professor of Linguistics, of Computer Science and Senior Fellow at the Stanford Institute for HAI
BioChristopher Manning is the inaugural Thomas M. Siebel Professor of Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). His research goal is computers that can intelligently process, understand, and generate human languages. Manning was an early leader in applying Deep Learning to Natural Language Processing (NLP), with well-known research on the GloVe model of word vectors, attention, machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, sentiment analysis, and summarization. He also focuses on computational linguistic approaches to parsing, natural language inference and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies. Manning has coauthored leading textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), as well as linguistic monographs on ergativity and complex predicates. His online CS224N Natural Language Processing with Deep Learning videos have been watched by hundreds of thousands of people. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). His research has won ACL, Coling, EMNLP, and CHI Best Paper Awards, and an ACL Test of Time Award. He has a B.A. (Hons) from The Australian National University and a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023, and he held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford. He is the founder of the Stanford NLP group (@stanfordnlp) and manages development of the Stanford CoreNLP and Stanza software.
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David Mazieres
Professor of Computer Science
BioMazieres investigates ways to improve the security of operating systems, file systems, and distributed systems. In addition, he has worked on large-scale peer-to-peer systems and e-mail privacy.
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Jay McClelland
Lucie Stern Professor in the Social Sciences, Professor of Psychology and, by courtesy, of Linguistics and of Computer Science
On Leave from 04/01/2024 To 06/30/2024Current Research and Scholarly InterestsMy research addresses topics in perception and decision making; learning and memory; language and reading; semantic cognition; and cognitive development. I view cognition as emerging from distributed processing activity of neural populations, with learning occurring through the adaptation of connections among neurons. A new focus of research in the laboratory is mathematical cognition and reasoning in humans and contemporary AI systems based on neural networks.
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Azalia Mirhoseini
Assistant Professor of Computer Science
BioAzalia Mirhoseini is an Assistant Professor in the Computer Science Department at Stanford University. Professor Mirhoseini's research interest is in developing capable, reliable, and efficient AI systems for solving high-impact, real-world problems. Her work includes generalized learning-based methods for decision-making problems in systems and chip design, self-improving AI models through interactions with the world, and scalable deep learning optimization. Prior to Stanford, she spent several years in industry AI labs, including Anthropic and Google Brain. At Anthropic, she worked on advancing the capabilities and reliability of large language models. At Google Brain, she co-founded the ML for Systems team, with a focus on automating and optimizing computer systems and chip design. She received her BSc degree in Electrical Engineering from Sharif University of Technology and her PhD in Electrical and Computer Engineering from Rice University. Her work has been recognized through the MIT Technology Review’s 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship venues such as Nature, and coverage by various media outlets, including MIT Technology Review, IEEE Spectrum, The Verge, The Times, ZDNet, VentureBeat, and WIRED.
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John Mitchell
Mary and Gordon Crary Family Professor in the School of Engineering, and Professor, by courtesy, of Electrical Engineering and of Education
Current Research and Scholarly InterestsProgramming languages, computer security and privacy, blockchain, machine learning, and technology for education
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Juan Carlos Niebles
Sr Research Engineer, Computer Science
Current Research and Scholarly InterestsThe goal of my research is to enable computers and robots to perceive the visual world by developing novel computer vision algorithms for automatic analysis of images and videos. We tackle fundamental open problems in computer vision research related to the visual recognition and understanding of human actions and activities, objects, scenes, and events. We also develop systems that solve practical world problems by introducing cutting-edge computer vision technologies into new domains.
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Aina Niemetz
Senior Research Engineer
Biohttps://cs.stanford.edu/people/niemetz
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Kunle Olukotun
Cadence Design Systems Professor, Professor of Electrical Engineering and of Computer Science
BioKunle Olukotun is the Cadence Design Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. He founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multi-core processor, called Niagara, was acquired by Sun Microsystems and now powers Oracle's SPARC-based servers. In 2017, Olukotun co-founded SambaNova Systems, a Machine Learning and Artificial Intelligence company, and continues to lead as their Chief Technologist.
Olukotun is the Director of the Pervasive Parallel Lab and a member of the Data Analytics tor What's Next (DAWN) Lab, developing infrastructure for usable machine learning. He is a member of the National Academy of Engineering, an ACM Fellow, and an IEEE Fellow for contributions to multiprocessors on a chip design and the commercialization of this technology. He also received the Harry H. Goode Memorial Award.
Olukotun received his Ph.D. in Computer Engineering from The University of Michigan. -
John Ousterhout
Leonard Bosack and Sandy K. Lerner Professor of Engineering, Professor of Computer Science and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsOusterhout's research ranges across a variety of topics in system software, software development tools, and user interfaces. His current research is in the area of granular computing: new software stack layers that allow the execution of large numbers of very small tasks (as short as a few microseconds) in a datacenter. Current projects are developing new techniques for thread management, network communication, and logging.
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Marco Pavone
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering and 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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Roy Pea
Director, H-STAR, David Jacks Professor of Education and Professor, by courtesy, of Computer Science
Current Research and Scholarly Interestslearning sciences focus on advancing theories, research, tools and social practices of technology-enhanced learning of complex domains
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Serge Plotkin
Associate Professor of Computer Science, Emeritus
BioPlotkin's focus is on optimization problems that are encountered in the context of design, management, and maintenance of broadband communication networks. Currently his main effort in this area is concentrated on development of algorithms for network topology design, routing, capacity sizing, server placement, and fair resource allocation. His goal is to develop both offline strategies that can be used during network design stage, as well as online strategies that can be applied to optimize existing network infrastructure.
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Balaji Prabhakar
VMware Founders Professor of Computer Science, Professor of Electrical Engineering and, by courtesy, of Operations, Information and Technology at the Graduate School of Business
BioPrabhakar's research focuses on the design, analysis, and implementation of data networks: both wireline and wireless. He has been interested in designing network algorithms, problems in ad hoc wireless networks, and designing incentive mechanisms. He has a long-standing interest in stochastic network theory, information theory, algorithms, and probability theory.
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Christopher Re
Associate Professor of Computer Science
On Leave from 04/01/2024 To 06/30/2024Current Research and Scholarly InterestsAlgorithms, systems, and theory for the next generation of data processing and data analytics systems.
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Eric Roberts
The Charles Simonyi Professor in the School of Engineering, Emeritus
BioFrom 1990-2002, Roberts served as associate chair and director of undergraduate studies for the Computer Science Department before being appointed as Senior Associate Dean in the School of Engineering and later moving on to become Faculty Director for Interdisciplinary Science Education in the office of the VPUE.
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Mendel Rosenblum
Cheriton Family Professor and Professor of Electrical Engineering
On Leave from 10/01/2023 To 06/30/2024Current Research and Scholarly InterestsNext generation data centers
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Mehran Sahami
Tencent Chair of the of the Computer Science Department, James and Ellenor Chesebrough Professor and Senior Fellow, by courtesy, at the Freeman Spogli Institute for International Studies
BioMehran Sahami is Tencent Chair of the Computer Science Department and the James and Ellenor Chesebrough Professor in the School of Engineering. As a Professor (Teaching) in the Computer Science department, he is also a Bass Fellow in Undergraduate Education and previously served as the Associate Chair for Education in Computer Science. Prior to joining the Stanford faculty, he was a Senior Research Scientist at Google. His research interests include computer science education, artificial intelligence, and ethics. He served as co-chair of the ACM/IEEE-CS joint task force on Computer Science Curricula 2013, which created curricular guidelines for college programs in Computer Science at an international level. He has also served as chair of the ACM Education Board, an elected member of the ACM Council, and was appointed by California Governor Jerry Brown to the state's Computer Science Strategic Implementation Plan Advisory Panel.
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J Kenneth Salisbury, Jr.
Professor (Research) of Computer Science and of Surgery (Anatomy), Emeritus
BioSalisbury worked on the development of the Stanford-JPL Robot Hand, the JPL Force Reflecting Hand Controller, the MIT-WAM arm, and the Black Falcon Surgical Robot. His work with haptic interface technology led to the founding of SensAble Technology, producers of the PHANToM haptic interface and software. He also worked on the development of telerobotic systems for dexterity enhancement in the operating room. His current research focuses on human-machine interaction, cooperative haptics, medical robotics, and surgical simulation.
