School of Engineering
Showing 151-200 of 375 Results
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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
Adjunct Lecturer, 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
On Leave from 04/01/2025BioThe 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 InterestsI am investigating the biophysical mechanisms that govern the organization and function of adhesion GPCRs involved in the process of synapse formation. aGPCRs possess dual roles in cell adhesion and signaling. Despite their importance in processes like neuronal synapse formation and association with various neuropsychiatric disorders, the precise mechanisms governing their organization and function at the cell membrane remain enigmatic.
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Siddharth M. Bhatia
Undergraduate, Computer Science
BioUndergraduate studying Computer Science!
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Rohan Tan Bhowmik
Undergraduate, Electrical Engineering
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.
