Programs, Centers and Institutes
Showing 1-50 of 486 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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Juan Alonso
Vance D. and Arlene C. Coffman Professor and the James and Anna Marie Spilker Chair of the Department of Aeronautics and Astronautics
BioProf. Alonso is the founder and director of the Aerospace Design Laboratory (ADL) where he specializes in the development of high-fidelity computational design methodologies to enable the creation of realizable and efficient aerospace systems. Prof. Alonso’s research involves a large number of different manned and unmanned applications including transonic, supersonic, and hypersonic aircraft, helicopters, turbomachinery, and launch and re-entry vehicles. He is the author of over 200 technical publications on the topics of computational aircraft and spacecraft design, multi-disciplinary optimization, fundamental numerical methods, and high-performance parallel computing. Prof. Alonso is keenly interested in the development of an advanced curriculum for the training of future engineers and scientists and has participated actively in course-development activities in both the Aeronautics & Astronautics Department (particularly in the development of coursework for aircraft design, sustainable aviation, and UAS design and operation) and for the Institute for Computational and Mathematical Engineering (ICME) at Stanford University. He was a member of the team that currently holds the world speed record for human powered vehicles over water. A student team led by Prof. Alonso also holds the altitude record for an unmanned electric vehicle under 5 lbs of mass.
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Afshine Amidi
Adjunct Lecturer, Institute for Computational and Mathematical Engineering (ICME)
BioTeaching CME 295: Transformers & Large Language Models (https://cme295.stanford.edu/) and CME 296: DIffusion & Large Vision Models (https://cme296.stanford.edu/).
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Shervine Amidi
Adjunct Lecturer, Institute for Computational and Mathematical Engineering (ICME)
BioTeaching CME 295: Transformers & Large Language Models (https://cme295.stanford.edu/) and CME 296: DIffusion & Large Vision Models (https://
cme296.stanford.edu/). -
Amin Arbabian
Professor of Electrical Engineering
Current Research and Scholarly InterestsMy group's research covers RF circuits and system design for (1) biomedical, (2) sensing, and (3) Internet of Things (IoT) applications.
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Zhenan Bao
K. K. Lee Professor, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Materials Science and Engineering, of Chemistry, and of Bioengineering
BioZhenan Bao joined Stanford University in 2004. She is currently a K.K. Lee Professor in Chemical Engineering, and with courtesy appointments in Chemistry, Bioengineering and Material Science and Engineering. She was the Department Chair of Chemical Engineering from 2018-2022 and in 2025. She founded the Stanford Wearable Electronics Initiative (eWEAR) and is the current faculty director. Bao received her Ph.D. degree in Chemistry from The University of Chicago in 1995 and joined Bell Labs, Lucent Technologies. She became a Distinguished Member of Technical Staff in 2001. Professor Bao currently has more than 800 refereed publications and more than 80 US patents with a Google Scholar H-index 237.
Bao is a member of the US National Academy of Sciences, National Academy of Engineering, the American Academy of Arts and Sciences and the National Academy of Inventors. Bao was elected a foreign member of the Chinese Academy of Science in 2021. She is a Fellow of AAAS, ACS, MRS, SPIE, ACS POLY and ACS PMSE.
Bao is a member of the Board of Directors for the Camille and Dreyfus Foundation from 2022. She served as a member of Executive Board of Directors for the Materials Research Society and Executive Committee Member for the Polymer Materials Science and Engineering division of the American Chemical Society. She co-founded C3 Nano Co. (acquired by Du Pont) and PyrAmes, which have produced products used in commercial smartphones and hospitals, respectively. Multiple inventions from her lab have been licensed and served as foundational technologies for several additional start-ups.
Bao was a recipient of the VinFuture Prize Female Innovator 2022, ACS Award of Chemistry of Materials 2022, MRS Mid-Career Award in 2021, AICHE Alpha Chi Sigma Award 2021, ACS Central Science Disruptor and Innovator Prize in 2020, ACS Gibbs Medal in 2020, the Wilhelm Exner Medal from the Austrian Federal Minister of Science in 2018, the L'Oreal UNESCO Women in Science Award North America Laureate in 2017. She was awarded the ACS Applied Polymer Science Award in 2017, ACS Creative Polymer Chemistry Award in 2013 ACS Cope Scholar Award in 2011. She is a recipient of the Royal Society of Chemistry Beilby Medal and Prize in 2009, IUPAC Creativity in Applied Polymer Science Prize in 2008.
In Stanford, Bao has pioneered molecular design concepts and fabrication processes to advance the scope and applications of skin-inspired electronics. Her group discovered nano confinement effect of conjugated polymers in polymer blends, which established the fundamental foundation for skin-inspired electronic materials and devices. Her work has resulted in new materials and device solutions for soft robotics, wearable and implantable electronics for precision health, precision mental health and advanced tools for understanding neuroscience and treatment of neurodegenerative diseases. Building on chemical insights, her group has developed foundational materials and devices that enabled a new generation of skin-inspired soft electronics. They provide unprecedented opportunities for understanding human health through developing monitoring, diagnosis and treatment tools. Some examples include: a neuromorphic e-skin that can sense force and temperature and directly communicate with brain, a wireless wound healing patch, a soft NeuroString for simultaneous neurochemical monitoring in the brain and gut, soft high-density electrophysiological recording array, a meta-learned skin sensor for detailed body movements, a reconfigurable self-healing electronic skin. -
Clark Barrett
Mizuki Asano and Thomas McGrath Professor
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. -
Stacey Bent
Jagdeep & Roshni Singh Professor in the School of Eng, Professor of Energy Science and Eng, Senior Fellow at Precourt & Prof, by courtesy, of Electrical Eng, Materials Sci Eng & Chemistry
BioThe research in the Bent laboratory is focused on understanding and controlling surface and interfacial chemistry and applying this knowledge to a range of problems in semiconductor processing, micro- and nano-electronics, nanotechnology, and sustainable and renewable energy. Much of the research aims to develop a molecular-level understanding in these systems, and hence the group uses of a variety of molecular probes. Systems currently under study in the group include functionalization of semiconductor surfaces, mechanisms and control of atomic layer deposition, molecular layer deposition, nanoscale materials for light absorption, interface engineering in photovoltaics, catalyst and electrocatalyst deposition.
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Biondo Biondi
Barney and Estelle Morris Professor
Current Research and Scholarly InterestsResearch
My students and I devise new algorithms to improve the imaging of reflection seismic data. Images obtained from seismic data are the main source of information on the structural and stratigraphic complexities in Earth's subsurface. These images are constructed by processing seismic wavefields recorded at the surface of Earth and generated by either active-source experiments (reflection data), or by far-away earthquakes (teleseismic data). The high-resolution and fidelity of 3-D reflection-seismic images enables oil companies to drill with high accuracy for hydrocarbon reservoirs that are buried under two kilometers of water and up to 15 kilometers of sediments and hard rock. To achieve this technological feat, the recorded data must be processed employing advanced mathematical algorithms that harness the power of huge computational resources. To demonstrate the advantages of our new methods, we process 3D field data on our parallel cluster running several hundreds of processors.
Teaching
I teach a course on seismic imaging for graduate students in geophysics and in the other departments of the School of Earth Sciences. I run a research graduate seminar every quarter of the year. This year I will be teaching a one-day short course in 30 cities around the world as the SEG/EAGE Distinguished Instructor Short Course, the most important educational outreach program of these two societies.
Professional Activities
2007 SEG/EAGE Distinguished Instructor Short Course (2007); co-director, Stanford Exploration Project (1998-present); founding member, Editorial Board of SIAM Journal on Imaging Sciences (2007-present); member, SEG Research Committee (1996-present); chairman, SEG/EAGE Summer Research Workshop (2006) -
Jeannette Bohg
Associate Professor of Computer Science
On Partial Leave from 01/01/2026 To 06/30/2026BioJeannette 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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Ivo Bolsens
Adjunct Professor
BioDirector of System X and instructor for EE310
Ivo retired from AMD as Senior Vice-President Corporate Research and Advanced Development. He managed advanced hardware and software technology development, including future architectures and software stacks to enable emerging opportunities in the fields of AI and embedded computing. His team was also driving the university partnerships to create a thriving, global ecosystem for AMD technology in academia.
He joined AMD in 2022, as part of the Xilinx acquisition. At Xilinx, he served as the Chief Technology Officer in charge of corporate research. He joined Xilinx in 2001 from the Interuniversity Microelectronics Centre (IMEC), an international research center based in Belgium. At IMEC he was vice president leading the R&D of digital signal processing hardware and software. During his tenure at IMEC, he spun-out several successful startups in the field of SOC design tools and wireless systems.
He serves on the advisory boards of IMEC, the Engineering Departments of San Jose State University and Santa Clara University, and the Department of Electrical Engineering and Computer Sciences at UC Berkeley.
He received his Master’s degree and PhD degree (EE) from the KU Leuven university in Belgium. -
Stephen Boyd
Samsung Professor in the School of Engineering
BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University, and a member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.
Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).
Professor Boyd is the author of many research articles and four books: Introduction to Applied Linear Algebra: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with El Ghaoui, Feron, and Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.
He has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, for excellence in computational mathematical programming. In 2023, he was given the AACC Richard E. Bellman Control Heritage Award, the highest recognition of professional achievement for U.S. control systems engineers and scientists. In 2025, he was awarded the IFAC Nathaniel B. Nichols Medal.
He is a Fellow of the IEEE, SIAM, INFORMS, IFAC, and ACA, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, a foreign member of the Chinese Academy of Engineering, and a foreign member of the National Academy of Engineering of Korea. He has been invited to deliver more than 100 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.
He has developed and taught many undergraduate and graduate courses, including Signals & Systems, Linear Dynamical Systems, Convex Optimization, and a recent undergraduate course on Matrix Methods. His graduate convex optimization course attracts around 300 students from more than 20 departments. In 1991 he received an ASSU Graduate Teaching Award, and in 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering. In 2003, he received the AACC Ragazzini Education award, for contributions to control education. In 2016 he received the Walter J. Gores award, the highest award for teaching at Stanford University. In 2017 he received the IEEE James H. Mulligan, Jr. Education Medal, for a career of outstanding contributions to education in the fields of interest of IEEE, with citation "For inspirational education of students and researchers in the theory and application of optimization."
