Professor of computer science and applied mathematics as well as a high-performance computing expert with more than thirty years of experience. Has significant experience the application of deep-learning and big-data techniques to weather and climate science, personalized medicine, patient cohort analysis, and genomics. Expert in architecting computing systems for data-intensive and artificial intelligence applications, including by increasing the processor architecture efficiency through use of horizontal and vertical instruction fusion. Research interests include computational science, high-performance and high-productivity computing, parallel algorithms and architectures, scientific application development, computational and information systems and facilities, high-order numerical methods, scalable solvers, cluster and cloud computing, and immersive visualization.
Formal Education
- Ph.D. in Applied Mathematics, Brown University
- M.S. in Applied Mathematics, Brown University
- M.S. in Mathematics and Computer Science, University of Vermont
- B.S. in Physics, Duke University
Career Highlights
- Multiple-time recipient of prestigious computing awards
- Principal architect of a 2010-era University supercomputer that was among the most powerful of its time
- Former manager of high-performance computing operations at a major national research center
- Consortium leader for a major research center's acquisition and operation of a leading-edge supercomputer with 131,000 processors capable of performing 280 trillion operations per second
- Proposed, developed, and taught a graduate course on highperformance scientific computing
- Co-author of a software library for computational fluid dynamics calculations that is fast and scalable on platforms from laptops to supercomputers with applications including fluid flow, thermal convection, and combustion and a user community of hundreds of scientists and engineers in academia, laboratories and industry
- Co-developer of a parallel direct solution method for linear systems
- Lead designer of an SOA (service-oriented architecture) for a terrestrial ecosystem modeling system
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Frequently Asked Questions
What types of cases can this expert support?
This expert covers artificial intelligence, cloud computing, and signal processing. They can speak to disputes over distributed systems architecture, cloud infrastructure, data processing pipelines, and deep learning. Their 30+ years of experience centers on supercomputing and scientific computing systems.
What is this expert's technical background?
Ph.D. in applied mathematics from Brown, plus master's degrees in applied math and in math and computer science. They've spent 30+ years designing supercomputers, managing NCAR's major computing facilities, and winning the ACM Gordon Bell Prize twice—one of the highest honors in high-performance computing.
What technologies does this expert specialize in?
This expert codes in C, C++, Python, Perl, Fortran, and Matlab. On the domain side, they specialize in high-performance and parallel computing, deep learning, cluster and cloud architectures, big data processing, numerical methods, and scientific simulations.