Institute for Computational and Mathematical Engineering (ICME)

Showing 21-40 of 65 Results

  • Pat Hanrahan

    Pat Hanrahan

    Canon Professor in the School of Engineering and Professor of Electrical Engineering

    BioProfessor Hanrahan's current research involves rendering algorithms, high performance graphics architectures, and systems support for graphical interaction. He also has worked on raster graphics systems, computer animation and modeling and scientific visualization, in particular, volume rendering.

  • Kari Hanson

    Kari Hanson


    BioKari is a former technology executive with a passion for entrepreneurship, innovation, business strategy and making the world a better place. Having worked as a coach, investor, advisor, board member and CFO, she enjoys empowering students and entrepreneurs to thrive in life, the classroom and the marketplace.

  • Jerry Harris

    Jerry Harris

    The Cecil H. and Ida M. Green Professor in Geophysics, Emeritus

    Current Research and Scholarly InterestsBiographical Information
    Jerry M. Harris is the Cecil and Ida Green Professor of Geophysics and Associate Dean for the Office of Multicultural Affairs. He joined Stanford in 1988 following 11 years in private industry. He served five years as Geophysics department chair, was the Founding Director of the Stanford Center for Computational Earth and Environmental Science (CEES), and co-launched Stanford's Global Climate and Energy Project (GCEP). Graduates from Jerry's research group, the Stanford Wave Physics Lab, work in private industry, government labs, and universities.

    My research interests address the physics and dynamics of seismic and electromagnetic waves in complex media. My approach to these problems includes theory, numerical simulation, laboratory methods, and the analysis of field data. My group, collectively known as the Stanford Wave Physics Laboratory, specializes on high frequency borehole methods and low frequency labratory methods. We apply this research to the characterization and monitoring of petroleum and CO2 storage reservoirs.

    I teach courses on waves phenomena for borehole geophysics and tomography. I recently introduced and co-taught a new course on computational geosciences.

    Professional Activities
    I was the First Vice President of the Society of Exploration Geophysicists in 2003-04, and have served as the Distinguished Lecturer for the SPE, SEG, and AAPG.

  • Trevor Hastie

    Trevor Hastie

    John A. Overdeck Professor, Professor of Statistics and of Biomedical Data Sciences

    Current Research and Scholarly InterestsFlexible statistical modeling for prediction and representation of data arising in biology, medicine, science or industry. Statistical and machine learning tools have gained importance over the years. Part of Hastie's work has been to bridge the gap between traditional statistical methodology and the achievements made in machine learning.

  • Gianluca Iaccarino

    Gianluca Iaccarino

    Director, Institute for Computational and Mathematical Engineering and Professor of Mechanical Engineering

    Current Research and Scholarly InterestsComputing and data for energy, health and engineering

    Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
    My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.

    Multidisciplinary Teaching

    I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results.

  • Alexander Ioannidis

    Alexander Ioannidis

    Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
    Postdoctoral Scholar, Biomedical Data Sciences

    BioDr. Alexander Ioannidis (Ph.D., M.Phil) earned his Ph.D. from Stanford University in Computational and Mathematical Engineering, where he teaches machine learning and data science as an Adjunct Professor in the School of Engineering. He also has an M.S. in Management Science and Engineering (Optimization) from Stanford. Prior to Stanford, he worked in superconducting computing logic and quantum computing at Northrop Grumman. He graduated summa cum laude from Harvard University in Chemistry and Physics and earned an M.Phil from the Department of Applied Math and Theoretical Physics in Computational Biology, and Diploma in Greek, from the University of Cambridge. As a current research fellow in the Stanford School of Medicine, Department of Biomedical Data Science his work focuses on the design of algorithms and application of computational methods for problems in genomics, clinical data science, and precision health with a particular focus on underrepresented populations in Oceania and Latin America.

  • Doug James

    Doug James

    Professor of Computer Science and, by courtesy, of Music

    Current Research and Scholarly InterestsComputer graphics & animation, physics-based sound synthesis, computational physics, haptics, reduced-order modeling

  • Antony Jameson

    Antony Jameson

    Professor (Research) of Aeronautics and Astronautics, Emeritus

    BioProfessor Jameson's research focuses on the numerical solution of partial differential equations with applications to subsonic, transonic, and supersonic flow past complex configurations, as well as aerodynamic shape optimization.

  • Ramesh Johari

    Ramesh Johari

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

    BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).

  • Peter K. Kitanidis

    Peter K. Kitanidis

    Professor of Civil and Environmental Engineering

    BioKitanidis develops methods for the solution of interpolation and inverse problems utilizing observations and mathematical models of flow and transport. He studies dilution and mixing of soluble substances in heterogeneous geologic formations, issues of scale in mass transport in heterogeneous porous media, and techniques to speed up the decay of pollutants in situ. He also develops methods for hydrologic forecasting and the optimization of sampling and control strategies.

  • Ellen Kuhl

    Ellen Kuhl

    Walter B Reinhold Professor in the School of Engineering, Robert Bosch Chair of Mechanical Engineering, Professor of Mechanical Engineering and, by courtesy, of Bioengineering

    Current Research and Scholarly Interestscomputaitonal simulation of brain development, cortical folding, computational simulation of cardiac disease, heart failure, left ventricular remodeling, electrophysiology, excitation-contraction coupling, computer-guided surgical planning, patient-specific simulation

  • Sanjiva Lele

    Sanjiva Lele

    Edward C. Wells Professor of the School of Engineering and Professor of Mechanical Engineering

    BioProfessor Lele's research combines numerical simulations with modeling to study fundamental unsteady flow phemonema, turbulence, flow instabilities, and flow-generated sound. Recent projects include shock-turbulent boundary layer interactions, supersonic jet noise, wind turbine aeroacoustics, wind farm modeling, aircraft contrails, multi-material mixing and multi-phase flows involving cavitation. He is also interested in developing high-fidelity computational methods for engineering applications.

  • Adrian Lew

    Adrian Lew

    Professor of Mechanical Engineering

    BioProf. Lew's interests lie in the broad area of computational solid mechanics. He is concerned with the fundamental design and mathematical analysis of material models and numerical algorithms.

    Currently the group is focused on the design of algorithms to simulate hydraulic fracturing. To this end we work on algorithms for time-integration embedded or immersed boundary methods.

  • Ali Mani

    Ali Mani

    Associate Professor of Mechanical Engineering

    BioAli Mani is an associate professor of Mechanical Engineering at Stanford University. He is a faculty affiliate of the Center for Turbulence Research and a member of Institute for Computational and Mathematical Engineering at Stanford. He received his PhD in Mechanical Engineering from Stanford in 2009. Prior to joining the faculty in 2011, he was an engineering research associate at Stanford and a senior postdoctoral associate at Massachusetts Institute of Technology in the Department of Chemical Engineering. His research group builds and utilizes large-scale high-fidelity numerical simulations, as well as methods of applied mathematics, to develop quantitative understanding of transport processes that involve strong coupling with fluid flow and commonly involve turbulence or chaos. His teaching includes the undergraduate engineering math classes and graduate courses on fluid mechanics and numerical analysis.

  • Alison Marsden

    Alison Marsden

    Douglass M. and Nola Leishman Professor of Cardiovascular Diseases, and Professor of Pediatrics (Cardiology) and of Bioengineering

    Current Research and Scholarly InterestsThe Cardiovascular Biomechanics Computation Lab at Stanford develops novel computational methods for the study of cardiovascular disease progression, surgical methods, and medical devices. We have a particular interest in pediatric cardiology, and use virtual surgery to design novel surgical concepts for children born with heart defects.

  • Parviz Moin

    Parviz Moin

    Franklin P. and Caroline M. Johnson Professor in the School of Engineering

    BioMoin is the founding director of the Center for Turbulence Research. Established in 1987 as a research consortium between NASA and Stanford, Center for Turbulence Research is devoted to fundamental studies of turbulent flows. Center of Turbulence Research is widely recognized as the international focal point for turbulence research, attracting diverse groups of researchers from engineering, mathematics and physics. He was the founding director of the Institute for Computational and Mathematical Engineering at Stanford.

    Professor Moin pioneered the use of direct and Large Eddy Simulation techniques for the study of turbulence physics, control and modelling concepts and has written widely on the structure of turbulent shear flows. His current interests include: interaction of turbulent flows and shock waves, aerodynamic noise, hypersonic flows, propulsion, computational science, flow control, large eddy simulation. He is a co- Editor of the Annual Review of Fluid Mechanics and Associate Editor of Journal of Computational Physics, and on the editorial board of Physical Review Fluids.

  • Walter Murray

    Walter Murray

    Professor (Research) of Management Science and Engineering, Emeritus

    BioProfessor Murray's research interests include numerical optimization, numerical linear algebra, sparse matrix methods, optimization software and applications of optimization. He has authored two books (Practical Optimization and Optimization and Numerical Linear Algebra) and over eighty papers. In addition to his University work he has extensive consulting experience with industry, government, and commerce.

  • Sanjiv Narayan

    Sanjiv Narayan

    Professor of Medicine (Cardiovascular Medicine)

    Current Research and Scholarly InterestsDr. Narayan directs the Computational Arrhythmia Research Laboratory, whose goal is to define the mechanisms underlying complex human heart rhythm disorders, to develop bioengineering-focused solutions to improve therapy that will be tested in clinical trials. The laboratory has been funded continuously since 2001 by the National Institutes of Health, AHA and ACC, and interlinks a disease-focused group of clinicians, computational physicists, bioengineers and trialists.