School of Engineering
Showing 451-500 of 794 Results
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John Mitchell
Mary and Gordon Crary Family Professor in the School of Engineering, and Professor, by courtesy, of Electrical Engineering and of Education
Current Research and Scholarly InterestsProgramming languages, computer security and privacy, blockchain, machine learning, and technology for education
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Subhasish Mitra
William E. Ayer Professor of Electrical Engineering and Professor of Computer Science
BioSubhasish Mitra holds the William E. Ayer Endowed Chair Professorship in the Departments of Electrical Engineering and Computer Science at Stanford University. He directs the Stanford Robust Systems Group, serves on the leadership team of the Microelectronics Commons AI Hardware Hub, leads the Computation Focus Area of the Stanford SystemX Alliance, and is the Associate Chair (Faculty Affairs) of Stanford Computer Science. His research ranges across Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences. Results from his research group have influenced almost every contemporary electronic system and have inspired significant government and research initiatives in multiple countries. He has held several international academic appointments — the Carnot Chair of Excellence in NanoSystems at CEA-LETI in France, and Invited Professor at ETH and EPFL in Switzerland and University of Tokyo in Japan. Prof. Mitra also has consulted for major technology companies including AMD (XIlinx), Anthropic, Cisco, Google, Intel, Samsung, and Sony. He recently cofounded TenX Semi, a startup on AI autopilot for chip design.
In the field of Robust Computing, he has created many key approaches for circuit failure prediction, CASP on-line diagnostics, QED system validation, soft error resilience, and X-Compact test compression. Their adoption by industry is growing rapidly, in markets ranging from cloud computing to automotive systems, under various names such as Silicon Lifecycle Management, Predictive Health Monitoring, In-System Test, In-field Scan, In-fleet Scan. His X-Compact approach has proven essential to cost-effective manufacturing and high-quality testing of almost all contemporary digital systems. X-Compact and its derivatives enabled billions of dollars of cost savings across the industry.
In the field of NanoSystems, with his students and collaborators, he demonstrated several firsts: the first NanoSystems hardware among all beyond-silicon nanotechnologies for energy-efficient computing (the carbon nanotube computer), the first 3D NanoSystem with computation immersed in data storage, the first published end-to-end computing systems using resistive memories (Resistive RAM-based non-volatile computing systems delivering 10-fold energy efficiency versus embedded flash), and the first monolithic 3D integration combining heterogeneous logic and memory technologies in silicon foundry. These received wide recognition: cover of NATURE, several Highlights to the US Congress, and highlight as "important scientific breakthrough" by news organizations worldwide.
Prof. Mitra's honors include the Harry H. Goode Memorial Award (by IEEE Computer Society for outstanding contributions in the information processing field), Newton Technical Impact Award in EDA (test-of-time honor by ACM SIGDA and IEEE CEDA), the University Researcher Award (by Semiconductor Industry Association and Semiconductor Research Corporation to recognize lifetime research contributions), the EDAA Achievement Award (by European Design and Automation Association, for outstanding lifetime contributions to electronic design, automation and testing), the Intel Achievement Award (Intel’s highest honor), and the Distinguished Alumnus Award from the Indian Institute of Technology, Kharagpur. He and his students have published over 15 award-winning papers across 5 topic areas (technology, circuits, EDA, test, verification) at major venues including the Design Automation Conference, International Electron Devices Meeting, International Solid-State Circuits Conference, International Test Conference, Symposia on VLSI Technology/VLSI Circuits, and Formal Methods in Computer-Aided Design. Stanford undergraduates have honored him several times "for being important to them." He is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and a Foreign Member of Academia Europaea. -
Fernando Mujica
Adjunct Professor, Electrical Engineering
BioFernando Mujica is an Adjunct Professor in the Department of Electrical Engineering at Stanford University. He received the Ph.D. degree in electrical engineering from the Georgia Institute of Technology in 1999 and B.S. and M.S. degrees from Universidad Simón Bolivar in 1993 and 1995, respectively. Prof. Mujica's research interests are in the area of signal processing. He has been granted more than 25 US patents over a wide range of applications. Prof. Mujica was elected to the Tau Beta Pi Teaching Honor Roll in 2022.
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Reza Nasiri Mahalati
Adjunct Professor, Electrical Engineering
BioReza Nasiri Mahalati is an Adjunct Professor in the department of Electrical Engineering at Stanford University and a senior hardware design engineer at Apple Inc. His current work focuses on the development of new hardware technologies that enable more fluid human computer interactions. He received the B.S. degree in Electrical Engineering from the Sharif University of Technology, Tehran, Iran in 2008, and the M.S. and Ph.D. degrees in Electrical Engineering from Stanford University in 2010 and 2013, respectively. While at Stanford, his research focused on mode-division multiplexing in multi-mode optical fibers, fiber-based imaging, optimization and digital signal processing.
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Koosha Nassiri Nazif
Affiliate, Program-Pop, E.
BioDr. Koosha Nassiri Nazif received his Ph.D. in Electrical Engineering (Jan 2022) and his M.S. in Mechanical Engineering (2016) from Stanford University. Along the way, he worked at Apple (2019) on OLED/LCD displays and at HP Labs (2017) on 3D electronics thermal management. He is currently a post-doctoral scholar at Stanford developing novel flexible optoelectronic devices, including solar cells and wearable sensors, based on 2D transition metal dichalcogenides. https://www.arinna.xyz.
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Yoshio Nishi
Professor (Research) of Electrical Engineering, Emeritus
Current Research and Scholarly Interestsresistive switching nonvolatile memory mechanism, and 2D materials and devices
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Dwight Nishimura
Addie and Al Macovski Professor, Emeritus
Current Research and Scholarly Interestsmedical imaging, magnetic resonance imaging
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Frederick U Nitta
Ph.D. Student in Electrical Engineering, admitted Autumn 2024
BioFrederick received his B.S. with EE and Chemistry from Stanford (2024), alongside a co-term in MSE (2024) at Stanford. He completed his EE honors thesis with Prof. Krishna Saraswat and Prof. Eric Pop on the efficiency limits of transition metal dichalcogenide (TMD) solar cells, receiving the Firestone Medal for Excellence in Undergraduate Research. He is now pursuing his Ph.D. in EE, on 3R-phase TMDs and their bulk photovoltaic effect, and on the physics and applications of transition metal oxides. He is co-advised by Prof. Eric Pop and Prof. Andrew Mannix.
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Kunle Olukotun
Cadence Design Systems Professor, Professor of Electrical Engineering and of Computer Science
BioKunle Olukotun is the Cadence Design Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. He founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multi-core processor, called Niagara, was acquired by Sun Microsystems and now powers Oracle's SPARC-based servers. In 2017, Olukotun co-founded SambaNova Systems, a Machine Learning and Artificial Intelligence company, and continues to lead as their Chief Technologist.
Olukotun is the Director of the Pervasive Parallel Lab and a member of the Data Analytics tor What's Next (DAWN) Lab, developing infrastructure for usable machine learning. He is a member of the National Academy of Engineering, an ACM Fellow, and an IEEE Fellow for contributions to multiprocessors on a chip design and the commercialization of this technology. He also received the Harry H. Goode Memorial Award.
Olukotun received his Ph.D. in Computer Engineering from The University of Michigan.
