School of Engineering
Showing 301-350 of 763 Results
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Ali Keshavarzi
Adjunct Professor, Electrical Engineering
BioAli Keshavarzi, Ph.D. is an Adjunct Professor in Electrical Engineering at Stanford University. Ali is involved in scholarly research and is an advisor to Stanford SystemX IoE Research (IoE = Internet of Everything). Currently Ali is a DARPA program manager in Microsystems Technology Office (MTO) defining impactful research frontiers in microelectronics. Ali is working on Software Defined Hardware (SDH) Program and on Foundation Required for Novel Compute (FRANC) Program while defining new concepts to push research forward on the technology, computing architecture, and data-centric application domains. Before his current role at DARPA, Ali was working with DARPA as an advisor and subject matter expert on the Electronic Resurgence Initiative (ERI). Ali is a member of DARPA MTO Investor Working Board (IWB) and the Embedded Entrepreneurship Initiative (EEI). Ali is a principal and the founder of Leading Edge Research LLC, Los Altos, CA.
Ali is a technology visionary and a leader who has been at the forefront of technology innovation with a track record of delivering critical process technologies, devices, circuits, SoCs, and modules to the semiconductor industry. Ali was the Vice President of R&D and a Fellow at Cypress Semiconductor and held various positions at Intel, TSMC, and GLOBALFOUNDRIES in a variety of technical and leadership roles over 25 years. Ali was a visiting research professor at UC Berkeley from 2017 to 2018.
Ali is an IEEE Fellow. He has over 60 U.S. patents, over 70 peer reviewed papers, has received best-paper awards and the best-panel award at ISSCC, most paper citation awards from DAC and IEDM. He has served in TPC of IEDM and ISSCC and has been the general chair of ISLPED. He received the prestigious Intel Achievement Award (IAA). Ali was awarded a distinguished Outstanding Electrical and Computer Engineer (OECE) of Purdue University.
https://engineering.purdue.edu/ECE/InfoFor/Alums/OECE/2015/keshavarzi.html -
Asir Intisar Khan
Visiting Postdoctoral Scholar, Electrical Engineering
Affiliate, Program-Pop, E.BioAsir Intisar Khan is a Postdoctoral Scholar in the Electrical Engineering and Computer Science department at the University of California, Berkeley, working with Prof. Sayeef Salahuddin. He is also a visiting postdoctoral scholar at Electrical Engineering, Stanford with Prof. Eric Pop. Asir received his Ph.D. and M.S. from the Electrical Engineering department at Stanford University, supervised by Prof. Eric Pop, and collaborated very closely with Profs. H.-S. Philip Wong, Kenneth Goodson, and Krishna Saraswat.
His research effort and vision encompass exploring novel materials and their functionalities to enable energy-efficient memory, computing devices, and interconnects for 3D heterogeneous integration. His research has enabled the lowest-to-date switching current density in phase-change memory technology and has been featured in Forbes Magazine and IEEE Spectrum. He received the Best Student Paper award at the 2022 IEEE VLSI Technology Symposium and several Best Student Presentation Awards: 2022 MRS Fall Meeting, 2023 AVS Symposium Electronic Materials and Photonics Division, and 2023 SRC TECHCON. He has held Research Intern positions at TSMC and IBM TJ Watson Research Center. Asir is a recipient of the 2023 AVS Russell & Sigurd Varian Award, the 2022 IEEE EDS Ph.D. Student Fellowship and 2022 Materials Research Society (MRS) Gold Graduate Student Award, and Stanford Graduate Fellowship.
https://sites.google.com/view/asirintisarkhan16 -
Oussama Khatib
Weichai Professor and Professor, by courtesy, of Electrical Engineering
BioRobotics research on novel control architectures, algorithms, sensing, and human-friendly designs for advanced capabilities in complex environments. With a focus on enabling robots to interact cooperatively and safely with humans and the physical world, these studies bring understanding of human movements for therapy, athletic training, and performance enhancement. Our work on understanding human cognitive task representation and physical skills is enabling transfer for increased robot autonomy. With these core capabilities, we are exploring applications in healthcare and wellness, industry and service, farms and smart cities, and dangerous and unreachable settings -- deep in oceans, mines, and space.
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Butrus Khuri-Yakub
Professor (Research) of Electrical Engineering, Emeritus
BioButrus (Pierre) T. Khuri-Yakub is a Professor of Electrical Engineering at Stanford University. He received the BS degree from the American University of Beirut, the MS degree from Dartmouth College, and the Ph.D. degree from Stanford University, all in electrical engineering. His current research interests include medical ultrasound imaging and therapy, ultrasound neuro-stimulation, chemical/biological sensors, gas flow and energy flow sensing, micromachined ultrasonic transducers, and ultrasonic fluid ejectors. He has authored over 600 publications and has been principal inventor or co-inventor of 107 US and international issued patents. He was awarded the Medal of the City of Bordeaux in 1983 for his contributions to Nondestructive Evaluation, the Distinguished Advisor Award of the School of Engineering at Stanford University in 1987, the Distinguished Lecturer Award of the IEEE UFFC society in 1999, a Stanford University Outstanding Inventor Award in 2004, Distinguished Alumnus Award of the School of Engineering of the American University of Beirut in 2005, Stanford Biodesign Certificate of Appreciation for commitment to educate, mentor and inspire Biodesgin Fellows, 2011, and 2011 recipient of IEEE Rayleigh award.
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Meo Kittiwanich
Director of Student and Academic Affairs, Electrical Engineering - Student Services
Current Role at StanfordDirector of Student and Academic Service in the Electrical Engineering Department.
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Taeyoung Kong
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioTaeyoung is a Ph.D. student at Stanford University working with prof. Mark Horowitz in VLSI group and he is currently working within the AHA Agile Hardware Project. He is interested in hardware accelerator for deep learning / image processing and hardware design methodology. Taeyoung received a B.S. in Electrical and Computer Engineering from Seoul National University in 2017, and M.S. in Electrical Engineering from Stanford University in 2020.
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Kalhan Koul
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
BioKalhan Koul is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. Previously, he was a Digital Design Intern at Micron and Silicon Labs. He received a B.S. in Electrical Engineering Honors and a B.A. in Plan II Honors (Liberal Arts) from The University of Texas in 2018 and his M.S. in Electrical Engineering from Stanford University in 2021. During his PhD he has worked on three chip tapeouts. The first was Chimera, a DNN accelerator utilizing RRAM for low energy inference. The next was Amber, a coarse grained reconfigurable array (CGRA) optimized for image processing and machine learning applications. Finally, Kalhan led the tapeout of Onyx, a CGRA accelerating both dense and sparse kernels on the same fabric. His current research focuses on further improving the efficiency of the CGRA and extending its acceleration to end-to-end machine learning workloads.
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Gregory Kovacs
Professor of Electrical Engineering, Emeritus
Current Research and Scholarly InterestsHis present research areas include instruments for biomedical and biological applications including space flight, solid-state sensors and actuators, cell-based sensors for toxin detection and pharmaceutical screening, microfluidics, electronic interfaces to tissue, and biotechnology, all with emphasis on solving practical problems.
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Christoforos Kozyrakis
Professor of Electrical Engineering and of Computer Science
BioChristos Kozyrakis is a Professor of Electrical Engineering and Computer Science at Stanford University. His primary research areas are computer architecture and computer systems. His current work focuses on cloud computing, systems for machine learning, and machine learning for systems. Christos leads the MAST research group. He is also the faculty director of the Stanford Platform Lab.
Christos holds a BS degree from the University of Crete and a PhD degree from the University of California at Berkeley. He is a fellow of the ACM and the IEEE. He has received the ACM SIGARCH Maurice Wilkes Award, the ISCA Influential Paper Award, the NSF Career Award, the Okawa Foundation Research Grant, and faculty awards by IBM, Microsoft, and Google. -
Renesmee Kuo
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
Masters Student in Electrical Engineering, admitted Autumn 2023BioRenesmee Kuo is an Electrical Engineering PhD candidate at Stanford University supported by NSF GRFP. She focuses on preclinical PET imaging for neuroinflammatory diseases and cancer in Prof. Michelle James' lab. She graduated from UC Berkeley with a BS in Bioengineering. Her research interests lie at the intersection of engineering and medicine. At UC Berkeley, she worked in Prof. Steve Conolly's lab on Magnetic Particle Imaging (MPI). She focused on tracking CAR-T cells in immunotherapy using high-resolution MPI tracers. She also focused on using commercially available high-resolution MPI tracers for early diagnosis of Pulmonary Embolisms and Cardiovascular disease in preclinical settings.
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Sanjay Lall
Professor of Electrical Engineering
On Leave from 04/01/2024 To 06/30/2024BioSanjay Lall is Professor of Electrical Engineering in the Information Systems Laboratory and Professor of Aeronautics and Astronautics at Stanford University. He received a B.A. degree in Mathematics with first-class honors in 1990 and a Ph.D. degree in Engineering in 1995, both from the University of Cambridge, England. His research group focuses on algorithms for control, optimization, and machine learning. Before joining Stanford he was a Research Fellow at the California Institute of Technology in the Department of Control and Dynamical Systems, and prior to that he was a NATO Research Fellow at Massachusetts Institute of Technology, in the Laboratory for Information and Decision Systems. He was also a visiting scholar at Lund Institute of Technology in the Department of Automatic Control. He has significant industrial experience applying advanced algorithms to problems including satellite systems, advanced audio systems, Formula 1 racing, the America's cup, cloud services monitoring, and integrated circuit diagnostic systems, in addition to several startup companies. Professor Lall has served as Associate Editor for the journal Automatica, on the steering and program committees of several international conferences, and as a reviewer for the National Science Foundation, DARPA, and the Air Force Office of Scientific Research. He is the author of over 130 peer-refereed publications.
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Anand Vikas Lalwani
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
BioAnand is a Graduate Student researcher in XLab (advisor: Debbie Senesky).
Anand's research work includes developing and deploying sensors for environmental and energy industries. Sensors developed include techniques for Hall Effect sensors to measure AC magnetic fields, deployable and low cost ammonia sensor for rivers and lakes, CO2 sensors for down-hole applications.
Anand's interests outside of research include startups and solving problems. Anand is committed to developing technologies that tackle pressing issues and translating work form lab into a startup. -
Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford Open Virtual Assistant Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.
Professor Lam's current research is on conversational virtual assistants with an emphasis on privacy protection. Her research uses deep learning to map task-oriented natural language dialogues into formal semantics, represented by a new executable programming language called ThingTalk. Her Almond virtual assistant, trained on open knowledge graphs and IoT API standards, can be easily customized to perform new tasks. She is leading an Open Virtual Assistant Initiative to create the largest, open, crowdsourced language semantics model to promote open access in all languages. Her decentralized Almond virtual assistant that supports fine-grain sharing with privacy has received Popular Science's Best of What's New Award in Security in 2019.
Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”. She was on the founding team of Tensilica, now a part of Cadence.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow.
