Stanford University
Showing 361-380 of 791 Results
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Siddharth Krishnan
Assistant Professor of Electrical Engineering, and by courtesy, of Bioengineering and of Materials Science and Engineering
Current Research and Scholarly InterestsThe Krishnan Lab develops bioelectronic devices, tools and systems for closed loop disease management. Our work is divided into the following broad areas:
1. Biohybrid electronics for therapy and sensing: we combine living cells as functional parts of implantable devices, leveraging their ability to produce complex biologic therapeutics in a constitutive or triggerable manner, and their ability to sense their complex dynamic environment. These efforts are focused on developed functional cures for diseases like Type I Diabetes and other conditions requiring the regular infusion of proteins, peptides or antibody drugs.
2. Digital drug release systems for particulate forms of biologic drugs: Many complex protein and peptide drugs are not stable in solution, thereby frustrating the ability to delivery them through pumps and autoinjectors. This need is particularly acute for drugs that need to be administered as emergency rescue therapies, such as glucagon in the context of type 1 Diabetes. We develop implantable, miniaturized microelectromechanical devices that can store particulate (powders, pills) forms of these drugs and release them in a close loop manner based on wireless inputs from sensors.
3. Wearable sensors: Wearables to detect biophysical (temperature, flow, cardiac activity) and biochemical markers of health are gaining importance for closed-loop disease management and personalized medicine. We design hardware for on-chip molecular profiling based on sampling biofluids in noninvasive or minimally invasive formats.
4. New wireless power architectures for implantable bioelectronics: We develop high-power, high-efficiency strongly coupled power harvesting system to power battery-free implant systems. -
Boran Kumral
Postdoctoral Scholar, Electrical Engineering
BioBoran Kumral is a postdoctoral scholar in Prof. Eric Pop's group in the Department of Electrical Engineering, where he focuses on nanoelectronics based on two-dimensional (2D) semiconductors. He holds a Ph.D. in Mechanical Engineering from the University of Toronto (2025), where he studied defect and strain engineering of 2D materials as an FRQ Doctoral Scholar, and a B.Eng. in Mechanical Engineering from McGill University (2018). He spent over a year working in industry between his undergraduate and graduate studies.
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Taesoo Kwon
Visiting Professor, Electrical Engineering
BioTaesoo Kwon is a Professor in the Department of Computer Science and Engineering at Seoul National University of Science and Technology (SeoulTech), Seoul, South Korea. He received his B.S. (2001), M.S. (2003), and Ph.D. (2007) degrees in Electrical Engineering from KAIST. He is currently on sabbatical leave as a Visiting Professor in the Department of Electrical Engineering at Stanford University (2026–2027). His research applies stochastic geometry to the modeling and performance analysis of wireless networks, with a current focus on AI-enabled networks and the optimization problems that arise in them.
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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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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering, Professor of Computer Science and, by courtesy, of Electrical Engineering
BioProfessor Lam's current research interest is to create effective and reliable AI assistants to accelerate the discovery of knowledge. Her OVAL lab has created numerous open-source LLM-based tools used by consumers, historians, and journalists in their work; currently, she is focusing on research assistants that can discover new insights for biomedicine and other technical areas.
Professor Lam's team has created the first quantifiably factual and engaging conversational agent, which has won the Best Research of the Year Award from Wikimedia Foundation; pioneered deep research agent called STORM that has been used by about a million users; developed the best-performing agent for retrieving knowledge from hybrid sources, including databases, knowledge graphs, and free-text, currently deployed at Wikimedia; created an agent framework that produces fluent task-oriented agents that do not hallucinate.
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.
