Computer Science
Showing 51-100 of 135 Results
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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
LeRa Professor and Professor, 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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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 compiler techniques that make high-level languages portable. He has received the NSF CAREER Award, the MIT EECS Sprowls PhD Thesis Award in Computer Science, the Tau Beta Phi 2024 Teaching Honor Roll, the Google ML and Systems Junior Faculty Awards, and several distinguished paper awards.
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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) -
Sanmi Koyejo
Assistant Professor of Computer Science
BioSanmi Koyejo is an Assistant Professor in the Department of Computer Science at Stanford University and an adjunct Associate Professor at the University of Illinois at Urbana-Champaign. He leads the Stanford Trustworthy AI Research (STAIR) lab, which develops measurement-theoretic foundations for trustworthy AI systems, spanning AI evaluation science, algorithmic accountability, and privacy-preserving machine learning, with applications to healthcare and scientific discovery. His research on AI capabilities evaluation has challenged conventional understanding in the field, including work on measurement frameworks cited in the 2024 Economic Report of the President.
Koyejo has received the Presidential Early Career Award for Scientists and Engineers (PECASE), Skip Ellis Early Career Award, Alfred P. Sloan Research Fellowship, NSF CAREER Award, and multiple outstanding paper awards at flagship venues, including NeurIPS and ACL. He has delivered keynote presentations at major conferences, including ECCV and FAccT. He serves in key leadership roles, including Board President of Black in AI, Board of Directors of the Neural Information Processing Systems Foundation, and other leadership positions in professional organizations advancing AI research and broadening participation in the field. -
Christoforos Kozyrakis
Leonard Bosack and Sandy K. Lerner Professor of Engineering and Professor of Computer Science
BioChristos Kozyrakis is the Leonard Bosack and Sandy K. Lerner Professor of Engineering and a Professor of Electrical Engineering and Computer Science at Stanford University. His primary research areas are computer architecture and computer systems. His current work focuses on cloud computing, systems for machine learning, and machine learning for systems.
Christos holds a BS degree from the University of Crete and a PhD degree from the University of California at Berkeley. He is a fellow of the ACM and the IEEE. He has received the ACM SIGARCH Maurice Wilkes Award, the ISCA Influential Paper Award, the NSF Career Award, the Okawa Foundation Research Grant, and faculty awards by IBM, Microsoft, and Google. -
Anshul Kundaje
Associate Professor of Genetics and of Computer Science
Current Research and Scholarly InterestsWe develop statistical and machine learning frameworks to model gene regulation and decipher the genetic and molecular basis of disease
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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering, Professor of Computer Science and, by courtesy, of Electrical Engineering
BioProfessor Lam's current research interest is to create effective and reliable AI assistants to accelerate the discovery of knowledge. Her OVAL lab has created numerous open-source LLM-based tools used by consumers, historians, and journalists in their work; currently, she is focusing on research assistants that can discover new insights for biomedicine and other technical areas.
Professor Lam's team has created the first quantifiably factual and engaging conversational agent, which has won the Best Research of the Year Award from Wikimedia Foundation; pioneered deep research agent called STORM that has been used by about a million users; developed the best-performing agent for retrieving knowledge from hybrid sources, including databases, knowledge graphs, and free-text, currently deployed at Wikimedia; created an agent framework that produces fluent task-oriented agents that do not hallucinate.
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 of Stanford Institute for Human-Centered AI, Anand Rajaraman and Venky Harinarayan Professor and Senior Fellow at the Stanford Institute for Human-Centered AI
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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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) Stanford Institute for Human-Centered AI, 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 08/31/2027Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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Percy Liang
Professor of Computer Science
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. 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), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
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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 Human-Centered AI
BioChristopher Manning is the inaugural Thomas M. Siebel Professor in 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). From 2010, Manning pioneered Natural Language Understanding and Inference using Deep Learning, with impactful research on sentiment analysis, paraphrase detection, the GloVe model of word vectors, attention, neural machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, and summarization, work for which he has received two ACL Test of Time Awards and the IEEE John von Neumann Medal (2024). He earlier led the development of empirical, probabilistic approaches to NLP, computational linguistics, and language understanding, defining and building theories and systems for Natural Language Inference, syntactic parsing, machine translation, and multilingual language processing, work for which he won ACL, Coling, EMNLP, and CHI Best Paper Awards. In NLP education, Manning coauthored foundational textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), and his online CS224N Natural Language Processing with Deep Learning course videos have been watched by hundreds of thousands. In linguistics, Manning is a principal developer of Stanford Dependencies and Universal Dependencies, and has authored monographs on ergativity and complex predicates. He is the founder of the Stanford NLP group (@stanfordnlp) and was an early proponent of open source software in NLP with Stanford CoreNLP and Stanza. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). Manning has a B.A. (Hons) from The Australian National University, a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023. He held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford.
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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
Current 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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Subhasish Mitra
William E. Ayer Professor of Electrical Engineering and Professor of Computer Science
BioSubhasish Mitra holds the William E. Ayer Endowed Chair Professorship in the Departments of Electrical Engineering and Computer Science at Stanford University. He directs the Stanford Robust Systems Group, serves on the leadership team of the Microelectronics Commons AI Hardware Hub funded by the US CHIPS and Science Act, leads the Computation Focus Area of the Stanford SystemX Alliance, and is the Associate Chair (Faculty Affairs) of Computer Science. His research ranges across Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences. Results from his research group have influenced almost every contemporary electronic system and have inspired significant government and research initiatives in multiple countries. He has held several international academic appointments — the Carnot Chair of Excellence in NanoSystems at CEA-LETI in France, Invited Professor at EPFL in Switzerland, and Visiting Professor at the University of Tokyo in Japan. Prof. Mitra also has consulted for major technology companies including AMD (XIlinx), Cisco, Google, Intel, Merck (EMD Electronics), and Samsung.
In the field of Robust Computing, he has created many key approaches for circuit failure prediction, CASP on-line diagnostics, QED system validation, soft error resilience, and X-Compact test compression. Their adoption by industry is growing rapidly, in markets ranging from cloud computing to automotive systems, under various names (Silicon Lifecycle Management, Predictive Health Monitoring, In-System Test Architecture, In-field Scan, In-fleet Scan). His X-Compact approach has proven essential to cost-effective manufacturing and high-quality testing of almost all 21st century systems. X-Compact and its derivatives enabled billions of dollars of cost savings across the industry.
In the field of NanoSystems, with his students and collaborators, he demonstrated several firsts: the first NanoSystems hardware among all beyond-silicon nanotechnologies for energy-efficient computing (the carbon nanotube computer), the first 3D NanoSystem with computation immersed in data storage, the first published end-to-end computing systems using resistive memories (Resistive RAM-based non-volatile computing systems delivering 10-fold energy efficiency versus embedded flash), and the first monolithic 3D integration combining heterogeneous logic and memory technologies in silicon foundry. These received wide recognition: cover of NATURE, several Highlights to the US Congress, and highlight as "important scientific breakthrough" by news organizations worldwide.
Prof. Mitra's honors include the Harry H. Goode Memorial Award (by IEEE Computer Society for outstanding contributions in the information processing field), Newton Technical Impact Award in EDA (test-of-time honor by ACM SIGDA and IEEE CEDA), the University Researcher Award (by Semiconductor Industry Association and Semiconductor Research Corporation to recognize lifetime research contributions), the EDAA Achievement Award (by European Design and Automation Association, for outstanding lifetime contributions to electronic design, automation and testing), the Intel Achievement Award (Intel’s highest honor), and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur. He and his students have published over 15 award-winning papers across 5 topic areas (technology, circuits, EDA, test, verification) at major venues including the Design Automation Conference, International Electron Devices Meeting, International Solid-State Circuits Conference, International Test Conference, Symposia on VLSI Technology/VLSI Circuits, and Formal Methods in Computer-Aided Design. Stanford undergraduates have honored him several times "for being important to them." He is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and a Foreign Member of Academia Europaea. -
Stephen B. Montgomery
Stanford Medicine Professor of Pathology, Professor of Genetics and of Biomedical Data Science and, by courtesy, of Computer Science
Current Research and Scholarly InterestsWe focus on understanding the effects of genome variation on cellular phenotypes and cellular modeling of disease through genomic approaches such as next generation RNA sequencing in combination with developing and utilizing state-of-the-art bioinformatics and statistical genetics approaches. See our website at http://montgomerylab.stanford.edu/
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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 and Professor of Computer Science, Emeritus
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, Senior Fellow at the Precourt Institute for Energy and Associate Professor, by courtesy, of Electrical Engineering & of Computer Science
BioDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University, where he directs the Autonomous Systems Laboratory and the Center for Automotive Research at Stanford. He is also a Distinguished Research Scientist at NVIDIA where he leads autonomous vehicle research. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a number of awards, including a Presidential Early Career Award for Scientists and Engineers from President Barack Obama, an Office of Naval Research Young Investigator Award, a National Science Foundation Early Career (CAREER) Award, a NASA Early Career Faculty Award, and an Early-Career Spotlight Award from the Robotics Science and Systems Foundation. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40. His work has been recognized with best paper nominations or awards at a number of venues, including the European Conference on Computer Vision, the IEEE International Conference on Robotics and Automation, the European Control Conference, the IEEE International Conference on Intelligent Transportation Systems, the Field and Service Robotics Conference, the Robotics: Science and Systems Conference, and the INFORMS Annual Meeting.
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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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Xiaojie Qiu
Assistant Professor of Genetics and, by courtesy, of Computer Science
Current Research and Scholarly InterestsAt the Qiu Lab, our mission is to unravel and predict the intricacies of gene regulatory networks and cell-cell interactions pivotal in mammalian cell fate transitions over time and space, with a special emphasis on heart evolution, development, and disease. We are a dynamic and interdisciplinary team, harnessing the latest advancements in machine learning as well as single-cell and spatial genomics by integrating the predictive power of systems biology with the scalability of machine learning,
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Priyanka Raina
Associate Professor of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsFor Priyanka's research please visit her group research page at https://stanfordaccelerate.github.io
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Christopher Re
Professor of Computer Science
Current 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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Sherri Rose
Professor of Health Policy and, by courtesy, of Computer Science
BioSherri Rose, Ph.D. is a Professor of Health Policy and, by courtesy, of Computer Science at Stanford University, where she is Director of the Health Policy Data Science Lab. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health. Within health policy, Dr. Rose works on algorithms in health care, risk adjustment, chronic kidney disease, and health program evaluation. She has published interdisciplinary projects across varied outlets, including Biometrics, Journal of the American Statistical Association, Journal of Health Economics, Health Affairs, and New England Journal of Medicine. In 2011, Dr. Rose coauthored the first book on machine learning for causal inference, with a sequel text released in 2018.
Dr. Rose has been honored with an NIH Director’s Pioneer Award, NIH Director's New Innovator Award, the ISPOR Bernie J. O'Brien New Investigator Award, and multiple mid-career awards, including the Gertrude M. Cox Award. She is a Fellow of the American Statistical Association (ASA) and received the Mortimer Spiegelman Award, which recognizes the statistician under age 40 who has made the most significant contributions to public health statistics. In 2024, she received both the ASHEcon Willard G. Manning Memorial Award for Best Research in Health Econometrics and the ASA Outstanding Statistical Application Award. She was recently awarded the Open Science Champion Prize by Stanford University. Her research has been featured in The New York Times, USA Today, and The Boston Globe. She was Co-Editor-in-Chief of the journal Biostatistics from 2019-2023. -
Mendel Rosenblum
Cheriton Family Professor and Professor of Electrical Engineering
Current Research and Scholarly InterestsNext generation data centers
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Amin Saberi
Professor of Management Science and Engineering and, by courtesy, of Computer Science
BioAmin Saberi is Professor of Management Science and Engineering at Stanford University. He received his B.Sc. from Sharif University of Technology and his Ph.D. from Georgia Institute of Technology in Computer Science. His research interests include algorithms, design and analysis of social networks, and applications. He is a recipient of the Terman Fellowship, Alfred Sloan Fellowship and several best paper awards.
Amin was the founding CEO and chairman of NovoEd Inc., a social learning environment designed in his research lab and used by universities such as Stanford as well as non-profit and for-profit institutions for offering courses to hundreds of thousands of learners around the world.
