School of Engineering
Showing 401-450 of 6,011 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.
