School of Engineering
Showing 641-660 of 808 Results
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Daniel Spielman
Professor of Radiology (Radiological Sciences Lab) and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsMy research interests are in the field of medical imaging, particularly magnetic resonance imaging and in vivo spectroscopy. Current projects include MRI and MRS at high magnetic fields and metabolic imaging using hyperpolarized 13C-labeled MRS.
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Tom A.D. Stone
Ph.D. Student in Electrical Engineering, admitted Autumn 2025
Current Research and Scholarly InterestsEEG Signal Processing for Clinical Neuroscience
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Maxwell Bradley Strange
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
BioMax is a Ph.D. student in Electrical Engineering advised by Mark Horowitz. His research focuses on developing infrastructure and tools to facilitate agile hardware development as part of the ongoing efforts by the Stanford AHA! Research Center. His research interests also include domain-specific hardware architectures, hardware/software co-design, and embedded systems design. He graduated from the University of Wisconsin in 2017 with a B.S. in Computer Engineering and Computer Science.
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Haotian Su
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioHaotian Su is a Ph.D. candidate in Electrical Engineering at Stanford University, co-advised by Prof. Eric Pop and Prof. Shan X. Wang. He received his B.S. in EE from National University of Singapore (2022). His research focuses on developing novel materials and thin films for energy-efficient memories and computing, including magnetic random-access memory (MRAM), oxide transistors, and other nanoscale devices.
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Thierry Tambe
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioThierry Tambe is an Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science, and the William George and Ida Mary Hoover Faculty Fellow at Stanford University. His research centers on co-designing algorithms and hardware—from high-level models down to custom silicon—to enable efficient execution of AI and data-intensive workloads, with memory efficiency as a central theme. His work has been recognized through an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, an NVIDIA Graduate PhD Fellowship, an IEEE SSCS Predoctoral Achievement Award, and several distinguished paper awards. Previously, Thierry was a visiting research scientist at NVIDIA and an engineer at Intel. He received a B.S. and M.Eng. from Texas A&M University, and a PhD from Harvard University, all in Electrical Engineering.
