School of Engineering
Showing 201-220 of 272 Results
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Peter Pinsky
Professor of Mechanical Engineering, Emeritus
BioPinsky works in the theory and practice of computational mechanics with a particular interest in multiphysics problems in biomechanics. His work uses the close coupling of techniques for molecular, statistical and continuum mechanics with biology, chemistry and clinical science. Areas of current interest include the mechanics of human vision (ocular mechanics) and the mechanics of hearing. Topics in the mechanics of vision include the mechanics of transparency, which investigates the mechanisms by which corneal tissue self-organizes at the molecular scale using collagen-proteoglycan-ion interactions to explain the mechanical resilience and almost perfect transparency of the tissue and to provide a theoretical framework for engineered corneal tissue replacement. At the macroscopic scale, advanced imaging data is used to create detailed models of the 3-D organization of collagen fibrils and the results used to predict outcomes of clinical techniques for improving vision as well as how diseased tissue mechanically degrades. Theories for mass transport and reaction are being developed to model metabolic processes and swelling in tissue. Current topics in the hearing research arena include multiscale modeling of hair-cell mechanics in the inner ear including physical mechanisms for the activation of mechanically-gated ion channels. Supporting research addresses the mechanics of lipid bilayer cell membranes and their interaction with the cytoskeleton. Recent past research topics include computational acoustics for exterior, multifrequency and inverse problems; and multiscale modeling of transdermal drug delivery. Professor Pinsky currently serves as Chair of the Mechanics and Computation Group within the Department of Mechanical Engineering at Stanford.
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Grigore Pintilie
Research Scientist
BioYork University, B.Sc. 1995-1999, Computer Science - Computer Graphics, HCI
University of Toronto, M.Sc. 1999-2001, Computer Science, Computer Graphics
Blueprint Initiative, 2001-2005 - Bioinformatics Research
MIT, Ph.D. 2005-2011 - Electrical Engineering and Computer Science, Biology - CryoEM map segmentation and fitting of atomic models
Baylor College of Medicine 2011-2017 - Scientific Programmer - Cryo-EM map analysis and atomic modeling
Stanford University 2017-present - Research Scientist - Cryo-EM map analysis and atomic modeling -
Serge Plotkin
Associate Professor of Computer Science, Emeritus
BioPlotkin's focus is on optimization problems that are encountered in the context of design, management, and maintenance of broadband communication networks. Currently his main effort in this area is concentrated on development of algorithms for network topology design, routing, capacity sizing, server placement, and fair resource allocation. His goal is to develop both offline strategies that can be used during network design stage, as well as online strategies that can be applied to optimize existing network infrastructure.
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Jim Plummer
John M. Fluke Professor of Electrical Engineering, Emeritus
Current Research and Scholarly InterestsGenerally studies the governing physics and fabrication technology of silicon integrated circuits, including the scaling limits of silicon technology, and the application of silicon technology outside traditional integrated circuits, including power switching devices such as IGBTs. Process simulation tools like SUPREM for simulating fabrication. Recent work has focused on wide bandgap semiconductor materials, particularly SiC and GaN, for power control devices.
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Nathan Liem Poag
Undergraduate, Electrical Engineering
BioEE major, saxophone enthusiast, skiing enthusiast, former ice hockey player, and semi-competitive SSBU player.
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Kilian M. Pohl, PhD
Professor (Research) of Psychiatry and Behavioral Sciences (Major Labs and Incubator) and, by courtesy, of Electrical Engineering
On Leave from 06/01/2026 To 08/31/2026Current Research and Scholarly InterestsThe foundation of the laboratory is computational science aimed at identifying biomedical phenotypes improving the mechanistic understanding, diagnosis, and treatment of neuropsychiatric disorders. The biomedical phenotypes are discovered by unbiased, machine learning-based searches across biological, neuroimaging, and neuropsychological data. This data-driven discovery currently supports the adolescent brain research of the NIH-funded National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). The laboratory also investigates brain patterns specific to alcohol use disorder, depression, and the human immunodeficiency virus (HIV) across the adult age range, and have advanced the understanding of a variety of brain diseases including schizophrenia, Alzheimer’s disease, glioma, and aging.
