School of Engineering


Showing 11-20 of 63 Results

  • Ron Dror

    Ron Dror

    Associate Professor of Computer Science and, by courtesy, of Molecular and Cellular Physiology and of Structural Biology

    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.

  • Eric Dunham

    Eric Dunham

    Associate Professor of Geophysics

    Current Research and Scholarly InterestsPhysics of natural hazards, specifically earthquakes, tsunamis, and volcanoes. Computational geophysics.

  • Charbel Farhat

    Charbel Farhat

    Vivian Church Hoff Professor of Aircraft Structures, Professor of Mechanical Engineering and Director of the Army High Performance Computing Research Center

    Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and high-performance software for the design and analysis of complex systems in aerospace, marine, mechanical, and naval engineering. They contribute major advances to Simulation-Based Engineering Science. Current engineering foci in research are on the nonlinear aeroelasticity and flight dynamics of Micro Aerial Vehicles (MAVs) with flexible flapping wings and N+3 aircraft with High Aspect Ratio (HAR) wings, layout optimization and additive manufacturing of wing structures, supersonic inflatable aerodynamic decelerators for Mars landing, and the reliable automated carrier landing via model predictive control. Current theoretical and computational emphases in research are on high-performance, multi-scale modeling for the high-fidelity analysis of multi-physics problems, high-order embedded boundary methods, uncertainty quantification, probabilistic machine learning, and efficient projection-based model order reduction as well as other forms of physics-based machine learning for time-critical applications such as design, active control, and digital twins.

  • Ron Fedkiw

    Ron Fedkiw

    Professor of Computer Science

    BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.

  • Oliver Fringer

    Oliver Fringer

    Professor of Civil and Environmental Engineering

    BioFringer's research focuses on the development and application of numerical models and high-performance computational techniques to the study of fundamental processes that influence the dynamics of the coastal ocean, rivers, lakes, and estuaries.

  • Margot Gerritsen

    Margot Gerritsen

    Professor of Energy Resources Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Civil and Environmental Engineering
    On Leave from 04/01/2021 To 06/30/2021

    Current Research and Scholarly InterestsResearch
    My work is about understanding and simulating complicated fluid flow problems. My research focuses on the design of highly accurate and efficient parallel computational methods to predict the performance of enhanced oil recovery methods. I'm particularly interested in gas injection and in-situ combustion processes. These recovery methods are extremely challenging to simulate because of the very strong nonlinearities in the governing equations. Outside petroleum engineering, I'm active in coastal ocean simulation with colleagues from the Department of Civil and Environmental Engineering, yacht research and pterosaur flight mechanics with colleagues from the Department of Mechanical and Aeronautical Engineering, and the design of search algorithms in collaboration with the Library of Congress and colleagues from the Institute of Computational and Mathematical Engineering.

    Teaching
    I teach courses in both energy related topics (reservoir simulation, energy, and the environment) in my department, and mathematics for engineers through the Institute of Computational and Mathematical Engineering (ICME). I also initiated two courses in professional development in our department (presentation skills and teaching assistant training), and a consulting course for graduate students in ICME, which offers expertise in computational methods to the Stanford community and selected industries.

    Professional Activities
    Senior Associate Dean, School of Earth, Energy and Environmental Sciences, Stanford (from 2015); Director, Institute for Computational and Mathematical Engineering, Stanford (from 2010); Stanford Fellow (2010-2012); Magne Espedal Professor II, Bergen University (2011-2014); Aldo Leopold Fellow (2009); Chair, SIAM Activity group in Geosciences (2007, present, reelected in 2009); Faculty Research Fellow, Clayman Institute (2008); Elected to Council of Society of Industrial and Applied Mathematics (SIAM) (2007); organizing committee, 2008 Gordon Conference on Flow in Porous Media; producer, Smart Energy podcast channel; Director, Stanford Yacht Research; Co-director and founder, Stanford Center of Excellence for Computational Algorithms in Digital Stewardship; Editor, Journal of Small Craft Technology; Associate editor, Transport in Porous Media; Reviewer for various journals and organizations including SPE, DoE, NSF, Journal of Computational Physics, Journal of Scientific Computing, Transport in Porous Media, Computational Geosciences; member, SIAM, SPE, KIVI, AGU, and APS

  • Kay Giesecke

    Kay Giesecke

    Professor of Management Science and Engineering
    On Partial Leave from 04/01/2021 To 06/30/2021

    Current Research and Scholarly InterestsKay is a financial technologist and engineer. He develops stochastic financial models, designs statistical methods for analyzing financial data, examines simulation and other numerical algorithms for solving the associated computational problems, and performs empirical analyses. Much of Kay's work is driven by important applications in areas such as credit risk management, investment management, and, most recently, housing finance.

  • Peter Glynn

    Peter Glynn

    Thomas W. Ford Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsStochastic modeling; statistics; simulation; finance

  • Ashish Goel

    Ashish Goel

    Professor of Management Science and Engineering and, by courtesy, of Computer Science

    BioAshish Goel is a Professor of Management Science and Engineering and (by courtesy) Computer Science at Stanford University. He received his PhD in Computer Science from Stanford in 1999, and was an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002. His research interests lie in the design, analysis, and applications of algorithms.

  • Catherine Gorle

    Catherine Gorle

    Assistant Professor of Civil and Environmental 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.