School of Engineering
Showing 501-550 of 5,933 Results
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Kwabena Boahen
Professor of Bioengineering and of Electrical Engineering
Current Research and Scholarly InterestsBoahen's group analyzes neural behavior computationally to elucidate principles of neural design at the cellular, circuit, and systems levels; and synthesizes neuromorphic electronic systems that scale energy-use with size as efficiently as the brain does. This interdisciplinary research program bridges neurobiology and medicine with electronics and computer science, bringing together these seemingly disparate fields.
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Alexandria Boehm
Richard and Rhoda Goldman Professor of Environmental Studies, Professor of Oceans and Senior Fellow at the Woods Institute for the Environment
BioI am interested in pathogens in the environment including their sources, fate, and transport in natural and engineered systems. I am interested in understanding of how pathogens are transmitted to humans through contact with water, feces, and contaminated surfaces. My research is focused on key problems in both developed and developing countries with the overarching goal of designing and testing novel interventions and technologies for reducing the burden of disease.
I am also interested broadly in coastal water quality where my work addresses the sources, transformation, transport, and ecology of biocolloids - specifically fecal indicator organisms, DNA, pathogens, and phytoplankton - as well as sources and fate of nitrogen. This knowledge is crucial to formulating new management policies and engineering practices that protect human and ecosystem health at the coastal margins. -
Jeannette Bohg
Associate 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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Adam Boies
Associate Professor of Mechanical Engineering and Center Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsSee www.ANEEStanford.com/research
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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. -
Emanuele Bombardi
Affiliate, Mechanical Engineering - Flow Physics and Computation
BioEmanuele Bombardi received his BSc (2020) and MSc (2022) degrees in Mathematical and Aerospace Engineering from the Politecnico di Torino. He subsequently began his doctoral studies at the Aéro-Thermo-Mécanique Laboratory at the Université libre de Bruxelles, under the supervision of Prof. Alessandro Parente and co-supervised by Prof. Luca Magri at Imperial College London, within the MODELAIR project funded by a Horizon Europe Marie Skłodowska-Curie Actions grant, with an expected graduation in 2027. He is a participant in the 2026 Summer Program at the Center for Turbulence Research at Stanford University.
Bombardi's research focuses on data assimilation methods for turbulence modelling and pollutant dispersion in urban atmospheric flows. Specific topics of interest include the development of ensemble Kalman filter frameworks for the calibration of turbulence closures, uncertainty quantification for low-fidelity simulations using high-fidelity data, and the application of these methods to complex urban environments. -
Dan Boneh
Cryptography Professor and Professor of Electrical Engineering
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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Ronaldo Borja
Professor of Civil and Environmental Engineering
BioBorja works in computational mechanics, geomechanics, and geosciences. His research includes developing strain localization and failure models for soils and rocks, modeling coupled solid deformation/fluid flow phenomena in porous materials, and finite element modeling of faulting, cracking, and fracturing in quasi-brittle materials.
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Mourad Bouache
Lecturer
BioMourad Bouache, Ph.D. is a pioneering computer scientist and tech leader operating at the critical intersection of hardware-software co-design, high-performance computing, and generative artificial intelligence.
Currently serving as the TPU and Models SW-HW Co-Design Tech Lead at Google, Mourad guides elite engineering teams tasked with architecting the next generation of accelerated AI infrastructure. His career spans over a decade of systemic evolution in AI, including serving as the Generative AI Engineering Tech Lead at Meta, driving core AI initiatives at Intel, and spending ten foundational years at Yahoo (through its Oath and Verizon chapters) scaling intelligent solutions across massive global ecosystems.
Anchored by deep academic roots, Mourad earned his Ph.D. in Computer Science from the University of Perpignan UPVD in France, followed by three prestigious postdoctoral fellowships focused on AI and Performance Optimization across the United States and Canada.
Committed to bridge-building between industry frontiers and academic excellence, he also serves as a lecturer at Stanford University, translating the complex realities of modern machine learning to inspire and equip the next generation of elite AI engineers. -
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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Tom Bowman
Professor of Mechanical Engineering, Emeritus
BioProfessor Bowman studies reacting flows, primarily through experimental means, and the processes by which pollutants are formed and destroyed in flames. In addition, he is interested in the environmental impact of energy use, specifically greenhouse gas emissions from use of fossil fuels.
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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."
