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David E. Keyes

Professor, Applied Mathematics and Computational Science

Principal Investigator, Hierarchical Computations on Manycore Architectures

Computer, Electrical and Mathematical Science and Engineering Division
Email icon david.keyes@kaust.edu.sa

Program Affiliations

Biography

David Keyes is a professor in the Applied Mathematics and Computational Sciences, Computer Science, and Mechanical Engineering programs. He served as a founding dean of the Mathematical and Computer Sciences and Engineering Division from 2009 to 2012 and as the director of the strategic initiative and ultimately the Research Center in Extreme Computing from 2013 to 2024. He is also an adjunct professor and former Fu Foundation Chair Professor of Applied Physics and Applied Mathematics at Columbia University, and a faculty affiliate of several laboratories of the U.S. Department of Energy.

Professor Keyes is Fellow of the Society for Industrial and Applied Mathematics (SIAM), the American Mathematical Society (AMS), and of the American Association for the Advancement of Science (AAAS). He is the recipient of the SIAM Prize for Distinguished Service to the Profession (2011), the Distinguished Faculty Teaching Award of Columbia University (2008), the Sidney Fernbach Award of IEEE Computer Society (2007), and the ACM Gordon Bell Prize (1999), and the Prize for Teaching Excellence in the Natural Sciences of Yale University (1991) .

Keyes graduated summa cum laude in Aerospace and Mechanical Sciences with a certificate in Engineering Physics from Princeton in 1978 and earned a doctorate in Applied Mathematics from Harvard in 1984. He was a Research Associate in Computer Science at Yale University 1984-1985, and has had decadal research appointments at the Institute for Computer Applications in Science and Engineering (ICASE), NASA-Langley Research Center, and the Institute for Scientific Computing Research (ISCR), Lawrence Livermore National Laboratory.

Research Interests

Keyes' research lies at the algorithmic interface between parallel computing and the numerical analysis of partial differential equations (PDEs), with a focus on scalable implicit solvers and nonlinear and linear preconditioning for large-scale applications in energy and environmental science on emerging for power-austere emerging architectures. 

Target applications demand high performance because of high resolution, high dimension, and high fidelity physical models and/or the “multi-solve” requirements of optimization, control, sensitivity analysis, inverse problems, data assimilation or uncertainty quantification. Newton-Krylov-Schwarz (NKS, 1994) and Additive Schwarz Preconditioned Inexact Newton (ASPIN, 2002) are methods he co-created and popularized. He also focuses on the discovery of data sparsity and the exploitation of hierarchy in large-scale systems involving dense covariance and kernel matrices in statistics, genomics, data science, and machine learning. 

Charters for his research are the International Exascale Software Project (IESP, 2011) and the Science-based Case for Large Scale Simulation (SCaLeS, 2001/2003) reports.
Keyword tag icon
machine learning quantum computing High Performance Computing scalable solvers software development

Education Profile

  • Ph.D. Applied Mathematics, Harvard University, 1984

  • M.S. Applied Mathematics, Harvard University, 1979

  • B.S. Engineering, Aerospace and Mechanical Sciences, Summa Cum Laude, Princeton University, 1978

  • Certificate, Program in Engineering Physics, Princeton University, 1978

Awards and Recognitions

  • Gordon Bell Prize for Climate Modelling, Association for Computing Machinery (ACM), 2024

  • Gauss Award for High Performance Computing, German Supercomputer Centers, 2020

  • Gordon Bell Prize, Association of Computing Machinery, 1999

  • Fellow, American Mathematical Society, 2012

  • Fellow, Society for Industrial and Applied Mathematics, 2011

  • SIAM Prize for Distinguished Service to the Profession, 2011

  • Distinguished Faculty Teaching Award, Columbia University, 2008

  • Sidney Fernbach Award, IEEE Computer Society, 2007

  • Prize for Teaching Excellence in the Natural Sciences, Yale University, 1991

  • Junior Faculty Fellowship, Yale University, 1990

  • NSF Presidential Young Investigator Award, 1989

  • Danforth Award for Excellence in Teaching, Harvard University, 1982

  • Hayes-Palmer Prize in Engineering, Princeton University, 1978

  • Career Achievement Award, Euro-Par Conference, 2018

Publications

  • R. Yokota, G. Turkiyyah & D. Keyes, "Communication Complexity of the Fast Multipole Method and its Algebraic Variants", Supercomput. Front. and Innov., 1:62–83, 2014.

  • D. Keyes et al. "Multiphysics Simulations: Challenges and Opportunities", Int. J. High Performance Computing Applications 27:5–83, 2013.

  • D. E. Keyes. "Exaflop/s – the Why and the How", Comptes Rendus 339:70–77, 2011.

  • D. A. Knoll & D. E. Keyes. "Jacobian-Free Newton-Krylov Methods: A Survey of Approaches and Applications", J. Comput. Phys., 193:357–397, 2004.

  • X.-C. Cai & D. E. Keyes. "Nonlinear Preconditioned Inexact Newton Algorithms", SIAM J. Sci. Comp. 24:183–200, 2002.

Research Areas

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