My motto is to outcompute. I am dedicated to placing simulation and data analytics on par with theory and experiment as modalities for making scientific discoveries, doing engineering design, and providing policy support.

#### Location

- Building 1, Office 0-116

#### News

#### Courses

- Professor Keyes' courses

#### Honors & Awards

- 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
- Gordon Bell Prize, Association of Computing Machinery, 1999
- 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

#### Education Profile

- PhD Applied Mathematics, Harvard University, 1984
- MS Applied Mathematics, Harvard University, 1979
- BS Engineering, Aerospace and Mechanical Sciences, Summa Cum Laude, Princeton University, 1978
- Certificate, Program in Engineering Physics, Princeton University, 1978

David Keyes is Professor of Applied Mathematics and Computational Science (AMCS) and the Director of the Extreme Computing Research Center (ECRC). He served as founding Dean of the CEMSE from 2009-2012. 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.

#### Research Interests

- Computer Science
- Applied Mathematics
- Algorithmic Interface
- Parallel Computing
- Partial Differential Equations
- PDE
- Big Data
- Computational Simulation
- Implicit Scalable Solvers

#### Education and early career

Keyes is 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. His research focus is in the algorithmic interface between parallel computing and the numerical analysis of partial differential equations (PDEs), with a focus on implicit scalable solvers for emerging architectures and their use in many large-scale applications in energy and environmental science.

#### Areas of expertise and current scientific interests

Keyes' interest is to advance in greatest memory capacities and fastest compute capabilities to tackle global problems productively. "We always have to push supercomputers to the next scale to obtain more resolution, and thus become more predictive with more complex systems. My effort is to build key portions – namely, scalable implicit algebraic solvers - of the open source software infrastructure for exascale computing, as in the G-8 countries’ International Exascale Software Roadmap.”

#### Career recognitions

Professor Keyes is Fellow of the American Mathematical Society (AMS), and of the Society for Industrial and Applied Mathematics (SIAM). He is the recipient of numerous honors such as the SIAM Prize for Distinguished Service to the Profession, 2011, the Distinguished Faculty Teaching Award, Columbia University, 2008, the Sidney Fernbach Award, IEEE Computer Society, 2007, the Gordon Bell Prize, Association of Computing Machinery, 1999 and the Prize for Teaching Excellence in the Natural Sciences, Yale University, 1991, to name a few.

#### Why supercomputing?

We always have to push supercomputers to the next scale to obtain more resolution, and thus become more predictive with more complex systems. My effort is to build key portions – namely, scalable implicit algebraic solvers - of the open source software infrastructure for exascale computing, as in the G-8 countries’ International Exascale Software Roadmap.

#### Why CEMSE?

Through the ECRC, Keyes now works on meeting the requirements of drastic reductions in communication and synchronization, increases in concurrency for cores sharing memory locally, local load redistribution, and algorithm-based fault tolerance. "CEMSE is simply the best place for research as it has no historical constraints that prevent us from building the world's first Computational Science and Engineering University, and bring it always a step further."