School of Engineering
Showing 101-200 of 336 Results
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Mohsen Bayati
Carl and Marilynn Thoma Professor in the Graduate School of Business and Professor, by courtesy, of Electrical Engineering and of Radiation Oncology (Radiation Therapy)
On Partial Leave from 2026-09-01 To 2026-12-31Current Research and Scholarly Interests1) Healthcare management: I am interested in improving healthcare delivery using data-driven modeling and decision-making.
2) Network models and message-passing algorithms: I work on graphical modeling ideas motivated from statistical physics and their applications in statistical inference.
3) Personalized decision-making: I work on machine learning and statistical challenges of personalized decision-making. The problems that I have worked on are primarily motivated by healthcare applications. -
Edward Bayliss
Graduate, Stanford Center for Professional Development
BioEmbedded Systems Engineer
Focused on building reliable, firmware and hardware systems across IoT and TinyML applications.
Strong experience in C-based development, hardware bring-up, and communication protocols (SPI, I2C, UART), with a focus on debugging and system integration.
Developed automated manufacturing test and programming infrastructure to improve reliability and scalability.
Currently completing the Electrical Engineering Graduate Certificate. -
David Beach
Professor (Teaching) of Mechanical Engineering, Emeritus
BioBeach teaches courses in the areas of design and manufacturing. Beach and Craig Milroy co-direct the Product Realization Laboratory which provides 1700 students annually with hands on experiences in product definition, conceptual design, detail design, and prototype creation. The PRL offers courses, mentors and tools in support of integrated designing and making. Pedagogically, Beach believes that creation of experience from which students (and teams of students) can interpret and internalize their own conclusions provides an excellent complement to content based teaching. His goal is to add strength in tacit knowledge which derives from the hands-on synthesis of design, prototype building, presentation and criticism.. The resulting judgment and instinct regarding materials, devices, materials transformation processes, and design process complement classical analytical engineering education to create superior engineers.
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Gill Bejerano
Professor of Developmental Biology, of Computer Science and of Pediatrics (Genetics)
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. -
Jeremy Benjamin
Associate Director of Development, Major Gifts, School of Engineering - External Relations
Current Role at StanfordTo work in concert with faculty and staff toward developing the necessary financial resources that will enable Stanford Medicine to achieve its mission of healing humanity through science.
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Noah Benjamin-Pollak
Ph.D. Student in Management Science and Engineering, admitted Autumn 2022
BioNoah Benjamin-Pollak (noahabp@stanford.edu) is a PhD candidate in Management Science & Engineering at Stanford University. He is a member of the Center for Work, Technology, and Organization (WTO). His research focuses on how different professions interact, particularly how authority and expertise are utilized in cross-occupational contexts. His current research uses ethnographic methods to understand cross-occupational collaboration between engineers and traditional business employees. Additionally, he is focused on understanding how expertise and expert authority are built and communicated between experts and non-expert audiences.
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Younes Bensouda Mourri
Affiliate, Computer Science
BioYounes was born and raised in Morocco. He currently teaches Artificial Intelligence on campus and online at Stanford University. He has worked on Coursera's #1 Course: Machine learning and #1 Specialization: Deep Learning. Younes co-created 3 Artificial Intelligence courses for graduate students at Stanford. He also designed and taught the Natural Language Processing Specialization on Coursera with Lukasz Kaiser.
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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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Michael Bernstein
Professor of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
BioMichael Bernstein is a Professor of Computer Science at Stanford University, where he is a Bass University Fellow and Senior Fellow at the Stanford Institute for Human-Centered Artificial Intelligence. A nationally bestselling author, Michael focuses on designing social, societal, and interactive technologies. This research has been reported in venues such as The New York Times, TED AI, and MIT Technology Review, and Michael himself has been recognized with an Alfred P. Sloan Fellowship and the Computer History Museum's Tech for Humanity Prize. Michael 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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Abrar Bhat
Postdoctoral Scholar, Chemical Engineering
Current Research and Scholarly InterestsBy integrating single-molecule biophysics, biochemical assays, cell-biological approaches, and advanced imaging, he is investigating the precise mechanisms that elucidate the precise role of Z-disc proteins in connecting altered levels of mechanical load to aberrant signaling and gene expression in human heart cells.
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Siddharth M. Bhatia
Undergraduate, Computer Science
BioUndergraduate studying Computer Science! My web site: https://sidmb.com/.
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Rohan Tan Bhowmik
Masters Student in Computer Science, admitted Autumn 2024
BioI am an undergraduate student at Stanford University studying Computer Science and Electrical Engineering with an emphasis on artificial intelligence. I am constantly seeking to learn and develop new machine-learning techniques and build applications based on them, especially in the areas of health, environment, and human-computer interaction. I’m especially interested in brain-inspired computing for energy-efficient systems.
As a software engineering intern at AMD AI Group since June 2024, I’ve gained expertise in machine learning compilers and optimized model performance across diverse hardware architectures. I unified AI/ML model implementations for high-performance computing on CPUs, GPUs, and AI accelerators. I also developed masked and causal attention modules on Torch-MLIR and IREE, enabling models like LLaMa and Stable Diffusion on the AMD stack.
My other recent projects include the development of 1) a wildfire prediction method by analyzing trends in environmental, meteorological, and geological data with an aim to mitigate the impact of California’s devastating wildfire seasons, 2) a respiratory disease exacerbation prediction system based on a novel spatio-temporal artificial intelligence algorithm and local environmental sensor network, 3) a machine learning technique for automating patient facial condition assessment and surgery planning, 4) blood alcohol level estimation using infrared imaging and deep neural networks, and 5) a novel image recognition framework utilizing a quantum optical convolutional neural network.
I have published papers based on my research in peer-reviewed journals, including the Journal of Environmental Management, IEEE Access, Electronics, and Facial Plastic Surgery & Aesthetic Medicine. I have won top national awards in the USA Physics, Astronomy & Astrophysics, Junior Math, Computing, and Biology Olympiads and was named Regeneron STS Top 300 Finalist in 2023.
Outside of academics, I play clarinet, tennis, and volunteer with organizations to help sensory-deficient individuals, including the Baker Institute for Children with Hearing Loss, Starkey Hearing Foundation, and VocaliD. -
Sarah Billington
UPS Foundation Professor, Professor of Civil and Environmental Engineering and Senior Fellow at the Woods Institute for the Environment
BioMy group's research is driven by two questions: how do built environments impact human wellbeing, and how can human-centered engineering design improve and amplify these wellbeing impacts? We examine how built features shape wellbeing across diverse populations and settings. These features range from access to nature and material choices to the use of ambient intelligence systems. With this knowledge, we develop tools, methods, and design interventions to improve wellbeing. We pursue this work through direct collaboration with those most affected, from older adults and caregivers to residents, communities, and the workers and practitioners who shape the built environment itself. In the past, my group focused on the design and evaluation of sustainable, durable construction materials including bio-based composites and ductile cement-based composites.
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Lacramioara Bintu
Associate Professor of Bioengineering
BioLacra Bintu is an Associate Professor of Bioengineering and a member of the Biophysics Program and Bio-X Institute at Stanford University. She earned undergraduate degrees in Physics, Mathematics, and Neuroscience from Brandeis University. As an undergraduate working with Jane Kondev and Rob Phillips, she used statistical mechanics to model transcription factor binding and gene regulation. She completed her Physics Ph.D. at U.C. Berkeley with Carlos Bustamante, where she used single-molecule approaches to study transcription on nucleosomal templates. As a postdoctoral scholar at Caltech with Michael Elowitz, she used live-cell microscopy to investigate chromatin-mediated gene regulation.
Her group seeks to discover fundamental principles of gene regulation and advance mammalian synthetic biology, with an emphasis on causal mechanisms, dynamic responses, and single-cell variability that enable signal integration at the population level. The lab develops tools to manipulate gene expression, for example by recruiting chromatin, transcriptional, or RNA regulators to defined genomic loci, or building DNA regulatory elements such as signal-responsive enhancers or silencers. To assess gene regulation responses at scale, the lab is using and developing new sequencing and imaging based techniques such as: delivery of large DNA libraries to cells coupled with sorting based on fluorescent and magnetic reporters, time-lapse fluorescence microscopy and in situ sequencing, or single-molecule footprinting of transcription factors and nucleosomes binding in live cells. Her group uses mathematical modeling to capture the fundamental principles underlying the observed gene expression responses and to predict new behaviors. This work provides insight into epigenetic mechanisms underlying development, cancer, and immune function and informs strategies for gene therapies that correct aberrant expression states.
Lacra lives in Menlo Park with her husband Anton and son Manu. They enjoy hiking, cooking, reading, playing board games, and watching birds in their backyard with their two cats. -
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) -
Nikola Blagojevic
Postdoctoral Scholar, Civil and Environmental Engineering
BioNikola Blagojević is a postdoctoral scholar at the Stanford Urban Resilience Initiative (SURI) within the Department of Civil and Environmental Engineering at Stanford University. His research focuses on regional recovery modeling and urban disaster resilience assessment.
As part of his doctoral work, Nikola developed pyrecodes, an open-source software for simulating how cities recover from disasters. His broader research interests span earthquake engineering, software development, post-disaster data collection, and climate risk and resilience assessment.
In addition to his academic research, Nikola has collaborated with the insurance industry to improve tools for assessing business interruption losses.
He holds a Ph.D. from ETH Zurich (2023) and an M.Sc. (2016) and B.Sc. (2015) in Structural Engineering from the University of Belgrade, Serbia. -
Juan Blanch
Sr Research Engineer, Program-Walter, T.
Current Research and Scholarly InterestsMy research focuses on the design of navigation integrity algorithms for safety critical applications (like air navigation and autonomous driving). I am interested in both the design of practical algorithms that provide the required safety margins, and in the theoretical limits on the performance of the integrity monitoring algorithms.
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Jose H. Blanchet
Professor of Management Science and Engineering
BioJose Blanchet is a Professor of Management Science and Engineering (MS&E) at Stanford and an Amazon Scholar. Prior to joining MS&E, he was a professor at Columbia (Industrial Engineering and Operations Research, and Statistics, 2008-2017), and before that he taught at Harvard (Statistics, 2004-2008). Jose is Fellow of the Institute of Mathematical Statistics. He is a recipient of the 2010 Erlang Prize and several best publication awards in areas such as applied probability, simulation, operations management, and revenue management. Jose also received a Presidential Early Career Award for Scientists and Engineers in 2010. He also has received numerous funding awards from various agencies and companies. He currently leads a Department of Defense Multi-University Research Initiative on extreme events. Jose has research interests in applied probability and Monte Carlo methods. He is the Editor in Chief of Mathematics of Operations Research. He has served on the editorial board of Advances in Applied Probability, Bernoulli, Extremes, Insurance: Mathematics and Economics, Journal of Applied Probability, Queueing Systems: Theory and Applications, and Stochastic Systems, among others.
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Steven G Blank
Adjunct Professor, Management Science and Engineering
BioSteve Blank is Adjunct Professor in the Department of Management Science and Engineering (MS&E) at Stanford University. He teaches courses on Lean Startups, innovation, and entrepreneurship in MS&E at Stanford.
In 2009 he was awarded the Stanford University Undergraduate Teaching Award in the department of Management Science and Engineering.
In 2013 his article "Why the Lean Startup Changes Everything" was the cover of the May 2013 Harvard Business Review
In 2014 the National Science Foundation and NCIIA awarded him the Outstanding Leadership Award for his work on developing the NSF Innovation Corps curriculum
In 2011 at the request of the National Science Foundation he modified ENG245, the Lean Launchpad class and it became the curriculum for the NSF Innovation-Corps..
In 2014 he developed the I-Corps@NIH curriculum to accelerate how research gets from the lab bench to the bedside for therapeutics, diagnostics and medical devices.
In 2016 he co-launched two new Management Science and Engineering (MS&E) classes at Stanford – MS&E 297 Hacking for Defense and its sister class – MS&E 298 Hacking for Diplomacy. He was on the list of the Thinkers50 ranking of top global management thinkers.
He has written 3 books including: The Four Steps to the Epiphany, The Startup Owners Manual (co-authored with Bob Dorf) and Holding a Cat By Its Tail.
His talk, The Secret History of Silicon Valley is often referred to as "the real story of how Silicon Valley started"
He blogs regularly at www.steveblank.com
