School of Engineering
Showing 641-660 of 794 Results
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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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Andreas Tolias
Professor of Ophthalmology and, by courtesy, of Electrical Engineering
BioAndreas Tolias is a faculty member at Stanford University, where he co-leads the Enigma Project. His research lies at the interface of neuroscience and AI, combining large-scale neuroscience experiments with machine learning to uncover the principles of natural intelligence. By focusing on perceptual inference and decision-making, his lab integrates systems and computational neuroscience with AI to decipher the network-level principles of intelligence. Dr. Tolias’s work aims to reverse-engineer these principles to create AI systems that are smarter, more robust, trustworthy, and efficient, while providing a powerful platform to test brain algorithms under complex natural tasks. He earned his B.A. and M.A. in Natural Sciences from the University of Cambridge, a Ph.D. in Systems and Computational Neuroscience from MIT, and completed postdoctoral training in Neuroscience and Machine Learning at the Max Planck Institute for Biological Cybernetics in Tübingen.
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Alice Tor
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
Grad Writing Tutor, Hume CenterBioPhD candidate in Electrical Engineering, advised by Dr. Paul Nuyujukian
