School of Engineering
Showing 601-700 of 789 Results
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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
BioDr. 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 InterestsClinical Applications of Magnetic Resonance Imaging
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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.
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Fouad Tobagi
Professor of Electrical Engineering
BioTobagi works on network control mechanisms for handling multimedia traffic (voice, video and TCP- based applications) and on the performance assessment of networked multimedia applications using user-perceived quality measures. He also investigates the design of wireless networks, including QoS-based media access control and network resource management, as well as network architectures and infrastructures for the support of mobile users, all meeting the requirements of multimedia traffic. He also investigates the design of metropolitan and wide area networks combining optical and electronic networking technologies, including topological design, capacity provisioning, and adaptive routing.
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Alexander Toews
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
Current Research and Scholarly InterestsMagnetic resonance imaging, computational imaging
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Alice Tor
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioPhD candidate in Electrical Engineering, advised by Dr. Paul Nuyujukian
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Caroline Trippel
Assistant Professor of Computer Science and of Electrical Engineering
BioCaroline Trippel is an Assistant Professor in the Computer Science and Electrical Engineering Departments at Stanford University, where she leads the High Assurance Computer Architectures Lab. Following her PhD, prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Trippel's research fits broadly in the area of computer architecture and focuses on promoting high assurance—correctness, security, and reliability—as a first-order computer architecture design goal. A central theme of her work is leveraging formal methods, especially automated reasoning, techniques to design and verify hardware systems. Trippel research has influenced the design of the RISC-V ISA memory consistency model both via her formal analysis of its draft specification and her subsequent participation in the RISC-V Memory Model Task Group; prompted Intel to update their Software Security Guidance to confirm that two Intel microarchitectures satisfy assumptions made by the Seberus Spectre defense that her lab developed; and produced a novel methodology and tool that synthesized two new variants of the famous Meltdown and Spectre attacks. Trippel's research has been recognized with IEEE Top Picks distinctions, a Sloan Research Fellowship, an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, the Intel Rising Star Faculty Award, an Intel Outstanding Researcher Award, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering, and more.
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Benjamin Van Roy
Professor of Electrical Engineering, of Management Science and Engineering and, by courtesy, of Computer Science
BioBenjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department's Graduate Teaching Award, and the Lanchester Prize. He was the plenary speaker at the 2019 Allerton Conference on Communications, Control, and Computing. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen. -
Jelena Vuckovic
Jensen Huang Professor of Global Leadership, Professor of Electrical Engineering and, by courtesy, of Applied Physics
Current Research and Scholarly InterestsJelena Vuckovic’s research interests are broadly in the areas of nanophotonics, quantum and nonlinear optics. Her lab develops semiconductor-based photonic chip-scale systems with goals to probe new regimes of light-matter interaction, as well as to enable platforms for future classical and quantum information processing technologies. She also works on transforming conventional photonics with the concept of inverse design, where optimal photonic devices are designed from scratch using computer algorithms with little to no human input. Her current projects include quantum and nonlinear optics, cavity QED, and quantum information processing with color centers in diamond and in silicon carbide, heterogeneously integrated chip-scale photonic systems, and on-chip laser driven particle accelerators.
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Brian A. Wandell
Isaac and Madeline Stein Family Professor and Professor, by courtesy, of Electrical Engineering, of Ophthalmology and of Education
Current Research and Scholarly InterestsModels and measures of the human visual system. The brain pathways essential for reading development. Diffusion tensor imaging, functional magnetic resonance imaging and computational modeling of visual perception and brain processes. Image systems simulations of optics and sensors and image processing. Data and computation management for reproducible research.
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Adam Wang
Assistant Professor of Radiology (Radiological Sciences Laboratory) and, by courtesy, of Electrical Engineering
BioMy research group develops technologies for advanced x-ray and CT imaging, including artificial intelligence for CT acquisition, reconstruction, and image processing; spectral imaging, including photon counting CT (PCCT) and dual-layer flat-panel detectors; novel system and detector designs; and their applications in diagnostic imaging and image-guided procedures. I am also the Director of the Photon Counting CT Lab, Zeego Lab, and Tabletop X-Ray Lab.
I completed my PhD in Electrical Engineering at Stanford, developing strategies for maximizing the information content of dual energy CT and photon counting detectors. I then pursued a postdoctoral fellowship at Johns Hopkins in the I-STAR Lab, developing reconstruction and registration methods for x-ray based image-guided surgery. I was then a Senior Scientist at Varian Medical Systems, developing x-ray/CT methods for image-guided radiation therapy, before returning to Stanford in 2018, where I now lead a comprehensive research program in advanced x-ray and CT imaging systems and methods, with funding from NIH, DOD, DOE, and industry partners. -
Shan X. Wang
Leland T. Edwards Professor in the School of Engineering and Professor of Electrical Engineering and, by courtesy, of Radiology (Molecular Imaging Program at Stanford)
Current Research and Scholarly InterestsShan Wang was named the Leland T. Edwards Professor in the School of Engineering in 2018. He directs the Center for Magnetic Nanotechnology and is a leading expert in Edge AI, biosensors, information storage and spintronics. His research and inventions span across a variety of areas including Edge AI, magnetic biochips, in vitro diagnostics, cancer biomarkers, magnetic nanoparticles, magnetic sensors, magnetoresistive random access memory, and magnetic integrated inductors.
