School of Engineering
Showing 161-170 of 582 Results
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Siegfried Glenzer
Professor of Photon Science and, by courtesy, of Mechanical Engineering
Current Research and Scholarly InterestsPlease see our website for detailed information: https://heds.slac.stanford.edu
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Abeynaya Gnanasekaran
Research Advisor, Mechanical Engineering - Mechanics and Computation
BioI am a PhD student in the Institute for Computational and Mathematical Engineering. My research interests lie in Numerical Linear Algebra and Parallel Computing. I'm working with Prof. Eric Darve on developing fast algorithms for general linear systems. I obtained my B.Tech (Honors) in Chemical Engineering from Indian Institute of Technology Madras, India.
I was born and brought up in Neyveli, an industrial town in south India. I enjoy listening to Indian music and reading novels. -
Kenneth Goodson
Vice Provost for Graduate Education and Postdoctoral Affairs, Davies Family Provostial Professor, and Professor, by courtesy, of Materials Science and Engineering
Current Research and Scholarly InterestsProf. Goodson’s Nanoheat Lab studies heat transfer in electronic nanostructures, microfluidic heat sinks, and packaging, focussing on basic transport physics and practical impact for industry. We work closely with companies on novel cooling and packaging strategies for power devices, portables, ASICs, & data centers. At present, sponsors and collaborators include ARPA-E, the NSF POETS Center, SRC ASCENT, Google, Intel, Toyota, Ford, among others.
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Catherine Gorle
Associate Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering
Current Research and Scholarly InterestsGorle's research focuses on the development of predictive flow simulations to support the design of sustainable buildings and cities. Specific topics of interest are the coupling of large- and small-scale models and experiments to quantify uncertainties related to the variability of boundary conditions, the development of uncertainty quantification methods for low-fidelity models using high-fidelity data, and the use of field measurements to validate and improve computational predictions.
