School of Engineering
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Professor of Mechanical Engineering
Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for engineering, surrogate and reduced order modeling, stochastic inversion, anomaly detection for engineering processes and manufacturing, numerical linear algebra, high-performance and parallel computing, and GPGPU.
Sr Research Engineer, Mechanical Engineering
University of Toronto Physics B.S (1978)
University of Toronto Aerospace Sciences M.Sc. (1980)
York University Physics Ph.D. (1986)
1986-present Senior Research Engineer, Mechanical Engineering Department
Dr. Davidson’s research interests span the fields of gas dynamics and combustion kinetics. During his tenure at Stanford University he has developed a wide array of optical and laser-based diagnostic methods for combustion chemistry and propulsion studies and has advanced the use of these diagnostics in shock tubes. He currently manages the shock tube operations in the High Temperature Gasdynamics Laboratories at Stanford University and actively mentors the approximately two dozen graduate students who use these facilities. He is a co-author of over 200 research publications and has been a member of the editorial advisory board for the International Journal of Chemical Kinetics and secretary of the Western States Section of the Combustion Institute.
An overview of the shock tube studies performed at Stanford under Prof. Hanson’s and Dr. Davidson’s supervision can be found in the six volumes entitled “Fundamental Kinetics Database Utilizing Shock Tube Measurements” available at http://purl.stanford.edu/kb621cw6967.
I am sort of retired, but apparently am still working.
Scott L. Delp, Ph.D.
Director, Wu Tsai Human Performance Alliance at Stanford, James H. Clark Professor in the School of Engineering, Professor of Bioengineering, of Mechanical Engineering and, by courtesy, of Orthopaedic Surgery
Current Research and Scholarly InterestsExperimental and computational approaches to study human movement. Development of biomechanical models to analyze muscle function, study movement abnormalities, design medical products, and guide surgery. Imaging and health technology development. Discovering the principles of peak performance to advance human health. Human performance research. Wearable technologies, video motion capture, and machine learning to enable large-scale analysis.
Masters Student in Mechanical Engineering, admitted Autumn 2022
BioNick Delurgio is a graduate student in Mechanical Engineering at Stanford University. Nick previously received his B.S. in Aerospace Engineering from the University of Texas at Austin, where he developed in interest in Guidance, Navigation, and Control (GNC) for Aerospace applications. At Stanford, Nick is pursuing his interest in GNC through autonomous systems research.