Stanford University
Showing 601-650 of 803 Results
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Debbie Senesky
Associate Professor of Aeronautics and Astronautics, of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy
BioDebbie G. Senesky is an Associate Professor at Stanford University in the Aeronautics and Astronautics Department and the Electrical Engineering Department. In addition, she is the Principal Investigator of the EXtreme Environment Microsystems Laboratory (XLab). Her research interests include the development of nanomaterials for extreme harsh environments, high-temperature electronics for Venus exploration, and microgravity synthesis of nanomaterials. In the past, she has held positions at GE Sensing (formerly known as NovaSensor), GE Global Research Center, and Hewlett Packard. She received the B.S. degree (2001) in mechanical engineering from the University of Southern California. She received the M.S. degree (2004) and Ph.D. degree (2007) in mechanical engineering from the University of California, Berkeley. Prof. Senesky is the Site Director of nano@stanford. She is currently the co-editor of two technical journals: IEEE Journal of Microelectromechanical Systems and Sensors. In recognition of her research, she received the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2025, Emerging Leader Abie Award from AnitaB.org in 2018, Early Faculty Career Award from the National Aeronautics and Space Administration (NASA) in 2012, Gabilan Faculty Fellowship Award in 2012, and Sloan Ph.D. Fellowship from the Alfred P. Sloan Foundation in 2004.
Prof. Senesky's career path and research has been featured by Scientific American, Seeker, People Behind the Science podcast, The Future of Everything radio show, Space.com, and NPR's Tell Me More program. More information about Prof. Senesky can be found at https://xlab.stanford.edu and on Instagram (@astrodebs). -
Kawin Setsompop
Professor of Radiology (Radiological Sciences Laboratory) and, by courtesy, of Electrical Engineering
BioKawin Setsompop is a Professor of Radiology and, by courtesy, of Electrical Engineering. His research focuses on the development of novel MRI acquisition methods, with the goal of creating imaging technologies that can be used to help better understand brain structure and function for applications in Healthcare and Health sciences. He received his Master’s degree in Engineering Science from Oxford University and his PhD in Electrical Engineering and Computer Science from MIT. Prior to joining Stanford, he was a postdoctoral fellow and subsequently a faculty at the A.A. Martinos center for biomedical imaging, MGH, as well as part of the Harvard and MIT faculty. His group has pioneered several widely-used MRI acquisition technologies, a number of which have been successfully translated into FDA-approved clinical products on Siemens, GE, Phillips, United Imaging and Bruker MRI scanners worldwide. These technologies are being used daily to study the brain in both clinical and neuroscientific fields.
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David Shim
Ph.D. Student in Electrical Engineering, admitted Autumn 2024
Current Research and Scholarly InterestsComputer Architecture, Robust Computing, Formal Verification, Machine Learning
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Constantine Sideris
Associate Professor of Electrical Engineering
BioConstantine Sideris is an Associate Professor of Electrical Engineering at Stanford University. Previously, he was an Assistant Professor at the University of Southern California from 2018 to 2025 and an Associate Professor from 2025 to 2026. He received the B.S., M.S., and Ph.D. degrees with honors from the California Institute of Technology in 2010, 2011, and 2017 respectively. He was a visiting scholar at UC Berkeley’s Wireless Research Center from 2013 to 2014. He was a postdoctoral fellow in the departments of Electrical Engineering and Computing and Mathematical Sciences at Caltech from January 2017 to August 2018.
He was the recipient of an ONR YIP award in 2023, an NSF CAREER award in 2021, an AFOSR YIP award in 2020, an AFOSR DURIP award in 2021, the Caltech Leadership Award in 2017, and an NSF graduate research fellowship in 2010. His research is highly interdisciplinary and bridges the fields of bioengineering, medicine, applied mathematics and computation with electrical engineering and physics.
His research interests include analog/RF integrated circuits, photonic integrated circuits, and computational electromagnetics for biomedical and biosensing applications and wireless communications. His current interests in biomedical devices include portable Point-of-Care in-vitro biosensors, wearable devices for real-time monitoring and analysis of biological signals, ingestible “smart” pills, and implantable devices. His current interests in computational electromagnetics include developing fast algorithms for simulating RF and nanophotonic devices and coupling them with efficient optimization algorithms to achieve the automated design of new, high-performance electromagnetic devices. -
Basile Simon
Affiliate, Program-Weissman T.
BioDirector, Law Program at the Starling Lab for Data Integrity (Stanford EE, USC).
Focus on the evidentiary value of integrity / provenance / authenticity data e.g. C2PA and Verifiable Credentials. OSI verification, U.S. federal authentication rules. Preservation of at-risk collections of evidence.
Advisory board at Airwars on technical and architectural matters and to the Visual Evidence Lab at CUBoulder. Technical advisor to the Hala Protocol on Audio. Resident at ECCHR law firm, and Investigative Commons collective. -
Karan P. Singh
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
Masters Student in Electrical Engineering, admitted Spring 2025BioI am a third-year electrical engineering PhD student and NSF Graduate Research Fellow in the Stanford Translational AI Lab (STAI), advised by Dr. Ehsan Adeli. I am broadly interested in applied ML, and am currently working on foundation models for functional MRI to better understanding aging and brain network interactions.
Previously, I was a post-baccalaureate researcher here at Stanford, where I applied machine learning to transcranial ultrasound neuromodulation, a non-invasive therapeutic modality with the potential to cure neurological diseases such as epilepsy, Alzheimer's, and even addiction. My primary focus during this time was using ML to improve therapy planning accuracy and efficiency. You can view more of my research on my website!
Outside of research, I enjoy playing the piano, badminton, calisthenics, and cooking! I am also a founder and president of the Stanford Piano Society. -
Richelle Smith
Postdoctoral Scholar, Electrical Engineering
BioRichelle L. Smith is a Postdoctoral Scholar at Stanford University with Professor Tom Lee. She received the B.S. and M.S. degrees in Electrical Engineering-Electrophysics from the University of Southern California (USC) in 2017, and the M.S. and Ph.D. degrees in Electrical Engineering from Stanford University in 2019 and 2024, respectively.
Her research interests include analog/mixed-signal circuit design and energy-efficient systems, with a focus on phase-domain communications and computing. Recent projects encompass oscillatory computing for combinatorial optimization, quantum computing emulation with oscillator circuits, brain-inspired/neuromorphic circuit design, as well as wireline transceivers and phase-domain/edge modulation signaling.
She has acted as a technical consultant to Rambus Labs. She has held internship positions at Linear Technology, Rambus Labs, Stanford Brains in Silicon Lab, TDK-InvenSense, and Silicon Laboratories. She holds 5 U.S. patents. Dr. Smith serves as a Reviewer for IEEE Transactions on Circuits and Systems—Part I: Regular Papers, IEEE Transactions on Circuits and Systems—Part II: Express Briefs, and IEEE Journal on Emerging and Selected Topics in Circuits and Systems.
Selected Awards:
• SPOTLIGHT paper, IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2024
• IEEE Solid-State Circuits Society (SSCS) Predoctoral Achievement Award, 2022–2023
• ARCS Foundation Northern California Fellowship (William K. Bowes, Jr. Foundation Scholar), 2022–2024
• Cadence Women in Technology Scholarship, 2021
• Analog Devices Outstanding Student Designer Award, 2019
• Stanford Graduate Fellowship (Sang Samuel Wang Scholar), 2017–2022
• NSF Graduate Research Fellowship, 2017–2022
• USC Discovery Scholar Prize, 2017
• Astronaut Scholarship, 2016
• Barry Goldwater Scholarship, 2016
• Tau Beta Pi Forge No. 42 Scholarship, 2015
• Rambus Innovator of the Future Scholarship, 2013
• USC Trustee Full Tuition Scholarship, 2013–2017 -
Hyongsok Tom Soh
W. M. Keck Foundation Professor of Electrical Engineering, Professor of Radiology (Diagnostic Sciences Laboratory) and of Bioengineering
On Partial Leave from 04/01/2026 To 06/30/2026BioDr. Soh received his B.S. with a double major in Mechanical Engineering and Materials Science with Distinction from Cornell University and his Ph.D. in Electrical Engineering from Stanford University. From 1999 to 2003, Dr. Soh served as the technical manager of MEMS Device Research Group at Bell Laboratories and Agere Systems. He was a faculty member at UCSB before joining Stanford in 2015. His current research interests are in analytical biotechnology, especially in high-throughput screening, directed evolution, and integrated biosensors.
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Olav Solgaard
Audrey S. Hancock Professor in the School of Engineering
BioThe Solgaard group focus on design and fabrication of nano-photonics and micro-optical systems. We combine photonic crystals, optical meta-materials, silicon photonics, and MEMS, to create efficient and reliable systems for communication, sensing, imaging, and optical manipulation.
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Michael A. Sommeling
Ph.D. Student in Electrical Engineering, admitted Autumn 2024
Masters Student in Electrical Engineering, admitted Spring 2026Current Research and Scholarly Interestsbrain-computer interface, electrophysiology, nanofabrication, retinal prosthesis
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Ethan Ruijian Song
Undergraduate, Electrical Engineering
Undergraduate, MusicBioTransfer EE Student from Duke.
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Shuran Song
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioShuran Song is an Assistant Professor of Electrical Engineering at Stanford University. Before joining Stanford, she was faculty at Columbia University. Shuran received her Ph.D. in Computer Science at Princeton University, BEng. at HKUST. Her research interests lie at the intersection of computer vision and robotics. Song’s research has been recognized through several awards, including the Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21, RSS’19, and finalists at RSS, ICRA, CVPR, and IROS. She is also a recipient of the NSF Career Award, Sloan Foundation fellowship as well as research awards from Microsoft, Toyota Research, Google, Amazon, and JP Morgan.
To learn more about Shuran’s work, please visit: https://shurans.github.io/ -
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.
