Joshua Booth, Ph.D.
Assistant Professor,
Computer Science
Biography
I research scalable systems and scientific computing for HPC. In particular, I focus on sparse linear algebra, graph algorithms, fault tolerance, power, and scheduling. I am working on integrating these topics into surrogate models, quantum computing, and AI at scale for scientific applications.
Education
- Ph.D. Computer Science and Engineering. The Pennsylvania State University 2014
- M.S. Computational Mathematics, Duquesne University 2010
- B.S. Applied Mathematics and Secondary Education, Robert Morris University 2007
Honors & Awards
- 2022 NSF Learning Fault Tolerance at Scale
- 2021. NSF Career Award: Fast, Energy Efficient Irregular Kernels via Neural Acceleration
- 2012. 3rd Place, ACM Graduate Student Research Competition, Super Computing 2012. Norm based ordering for reduced iterations using parallel incomplete Cholesky preconditioning.
- 2004. 1st Place, Oracle International JAVA Competition.