School of Engineering
Showing 351-400 of 792 Results
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Renesmee Kuo
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioRenesmee Kuo is an Electrical Engineering PhD candidate at Stanford University supported by NSF GRFP. Her research interests lie at the intersection of engineering and medicine. She focuses on validation of preclinical PET imaging tracers and their translation into the clinic for applications in neuroinflammatory diseases (e.g., MS, AD) and cancer (e.g., brain metastasis) in Prof. Michelle James' lab. She graduated from UC Berkeley with a BS in Bioengineering. At Berkeley, she worked in Prof. Steve Conolly's lab on Magnetic Particle Imaging (MPI), focusing on tracking CAR-T cells in immunotherapy using high-resolution MPI tracers. She also explored 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
BioSanjay 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. -
Jin Hyung Lee
Associate Professor of Neurology and Neurological Sciences (Neurology Research), of Neurosurgery and of Bioengineering and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsIn vivo visualization and control of neural circuits
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Thomas Lee
Professor of Electrical Engineering
BioProfessor Lee's principal areas of professional interest include analog circuitry of all types, ranging from low-level DC instrumentation to high-speed RF communications systems. His present research focus is on CMOS RF integrated circuit design, and on extending operation into the terahertz realm.
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Craig Levin
Professor of Radiology (Molecular Imaging Program at Stanford/Nuclear Medicine) and, by courtesy, of Physics, of Electrical Engineering and of Bioengineering
Current Research and Scholarly InterestsMolecular Imaging Instrumentation
Laboratory
Our research interests involve the development of novel instrumentation and software algorithms for in vivo imaging of cellular and molecular signatures of disease in humans and small laboratory animal subjects. -
Philip Levis
Professor of Computer Science and of Electrical Engineering
BioProfessor Levis' research focuses on the design and implementation of efficient software systems for embedded wireless sensor networks; embedded network sensor architecture and design; systems programming and software engineering.
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Axel Levy
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioAxel is a PhD candidate in Electrical Engineering at Stanford University. He is jointly supervised by Pr. Mike Dunne (LCLS, SLAC) and Pr. Gordon Wetzstein. His research focuses on solving inverse problems that arise in scientific imaging, that is to say getting as much information as possible about hidden physical quantities from noisy or sparsely sampled measurements.
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Meijin Li
Masters Student in Electrical Engineering, admitted Autumn 2023
BioI'm Meijin Li, a software engineering and machine learning enthusiast, deeply engrossed in the real-world applications of AI+. I am presently pursuing a Master's degree in Electrical Engineering at Stanford University, specializing in the software system track.
I work at the intersection of machine learning, software, and cloud engineering in recent internship at Alibaba and project at Stanford, all about building AI traning or powered platform. I have a strong passion for real-world applications of AI+. I'm actively seeking software engineer opportunities.
During my undergraduate years, I was fortunate to work under the guidance of Prof. Zhiyang F. on multiple Reinforcement Learning and Computer Systems research projects. Additionally, I had the opportunity to further enhance my skills during my recent internship at Alibaba, with the expert mentorship of Mr. Qingnan Y. Here I was involved in developing an enterprise-level CI/CD/CT Web platform for Large Language Model training, deployment, and testing.
I am excited to leverage my skills and knowledge to drive advancements in this ever-evolving field and contribute to AI+ practical applications. -
Samuel Low
Ph.D. Student in Aeronautics and Astronautics, admitted Winter 2023
Ph.D. Minor, Electrical Engineering
Student Employee, Summer SessionBioSamuel Low is a Ph.D. candidate in the Stanford Space Rendezvous Laboratory, advised by Professor Simone D'Amico. Sam graduated from Stanford with an M.S. in Aeronautics and Astronautics (2023) and from the Singapore University of Technology and Design (SUTD) with a B.Sc. in Engineering Product Development (2018). His broad interests are in the guidance, navigation, control and autonomy of distributed space systems, such as formations and swarm satellites. His research focus is on enabling precise and robust state estimation between distributed spacecraft, centered on sensor/data fusion with carrier phase differential GNSS, with immediate applications to flight missions such as the VISORS and SWARM-EX missions. He had worked previously in DSO National Laboratories, Singapore, on space mission design and on developing navigation algorithms for Singapore's first formation flying satellite mission. He received the DSO Postgraduate Fellowship (2021), the Tan Kah Kee Postgraduate Scholarship (2021), the DSO SOAR Scholarship (2017), and the Asian Leadership Program Scholarship (2015-2018) jointly awarded by SUTD and Zhejiang University. In his spare time, he enjoys photography, painting, and outdoor activities.
