School of Engineering
Showing 21-30 of 35 Results
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Jennifer Dionne
Professor of Materials Science and Engineering
BioJennifer Dionne is the Senior Associate Vice Provost of Research Platforms/Shared Facilities and an Associate Professor of Materials Science and Engineering and of Radiology (by courtesy) at Stanford. Jen received her Ph.D. in Applied Physics at the California Institute of Technology, advised by Harry Atwater, and B.S. degrees in Physics and Systems & Electrical Engineering from Washington University in St. Louis. Prior to joining Stanford, she served as a postdoctoral researcher in Chemistry at Berkeley, advised by Paul Alivisatos. Jen's research develops nanophotonic methods to observe and control chemical and biological processes as they unfold with nanometer scale resolution, emphasizing critical challenges in global health and sustainability. Her work has been recognized with the Alan T. Waterman Award (2019), an NIH Director's New Innovator Award (2019), a Moore Inventor Fellowship (2017), the Materials Research Society Young Investigator Award (2017), Adolph Lomb Medal (2016), Sloan Foundation Fellowship (2015), and the Presidential Early Career Award for Scientists and Engineers (2014), and was featured on Oprah’s list of “50 Things that will make you say ‘Wow!'"
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David Donoho
Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences
BioDavid Donoho is a mathematician who has made fundamental contributions to theoretical and computational statistics, as well as to signal processing and harmonic analysis. His algorithms have contributed significantly to our understanding of the maximum entropy principle, of the structure of robust procedures, and of sparse data description.
Research Statement:
My theoretical research interests have focused on the mathematics of statistical inference and on theoretical questions arising in applying harmonic analysis to various applied problems. My applied research interests have ranged from data visualization to various problems in scientific signal processing, image processing, and inverse problems. -
Persis Drell
Provost, Emerita, James and Anna Marie Spilker Professor, Professor of Materials Science and Engineering and of Physics
BioPersis Drell is the James and Anna Marie Spilker Professor in the School of Engineering, a professor of materials science and engineering, and a professor of physics. From Feb 1, 2017 to Sept. 30, 2023, Drell was the provost of Stanford University.
Prior to her appointment as provost in February 2017, she was dean of the Stanford School of Engineering from 2014 to 2017 and director of U.S. Department of Energy SLAC National Acceleratory Laboratory from 2007 to 2012.
She earned her bachelor’s degree in mathematics and physics from Wellesley College and her PhD in atomic physics from UC Berkeley. Before joining the faculty at Stanford in 2002, she was a faculty member in the physics department at Cornell University for 14 years. -
Leora Dresselhaus-Marais
Assistant Professor of Materials Science and Engineering, of Photon Science and, by courtesy, of Mechanical Engineering
Current Research and Scholarly InterestsMy group develops new methods to update old processes in metals manufacturing
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Ron Dror
Cheriton Family Professor and Professor, by courtesy, of Structural Biology and of Molecular & Cellular Physiology
Current Research and Scholarly InterestsMy lab’s research focuses on computational biology, with an emphasis on 3D molecular structure. We combine two approaches: (1) Bottom-up: given the basic physics governing atomic interactions, use simulations to predict molecular behavior; (2) Top-down: given experimental data, use machine learning to predict molecular structures and properties. We collaborate closely with experimentalists and apply our methods to the discovery of safer, more effective drugs.
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Shaul Druckmann
Associate Professor of Neurobiology, of Psychiatry and Behavioral Sciences and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsOur research goal is to understand how dynamics in neuronal circuits relate and constrain the representation of information and computations upon it. We adopt three synergistic strategies: First, we analyze neural circuit population recordings to better understand the relation between neural dynamics and behavior, Second, we theoretically explore the types of dynamics that could be associated with particular network computations. Third, we analyze the structural properties of neural circuits.
