Sarat Sreepathi is a Computer Scientist interested in interdisciplinary research at the intersection of High Performance Computing and domain sciences. He is a member of the Computational Earth Sciences Group in the Computational Sciences and Engineering Division at Oak Ridge National Laboratory. He received his Ph.D. in Computer Science from North Carolina State University. He is a Senior member of ACM and IEEE.

He currently serves on the SciDAC (Scientific Discovery through Advanced Computing) Coordination Committee, NERSC (National Energy Research Scientific Computing Center) User Group Executive Committee and previously served as the Chair of the OLCF (Oak Ridge Leadership Computing Facility) User Group Executive Board (2020-2021).

He is the Performance Coordinator for the Energy Exascale Earth System Model (E3SM) project, United States Department of Energy’s flagship climate modeling effort. He leads application co-design efforts as a member of the Exascale Computing Project (ECP) application teams (Climate: E3SM-MMF and Nuclear Fusion: XGC). He is the Computational Readiness Lead and Co-PI for Innovative and Novel Computational Impact on Theory and Experiment (INCITE) supercomputer allocations for XGC and E3SM projects respectively.

His research interests include High Performance Computing, Computational Climate Science, Performance Analytics, Exascale Co-design, Optimization Algorithms, Computational Intelligence, Parallel I/O, Performance Analysis and Optimization.

* 15+ years of experience in design and development of efficient parallel scientific applications on leadership class supercomputers.



Sarat's picture
Sarat Sreepathi
Computer Scientist
Computational Earth Sciences Group
Computational Sciences and Engineering Division
Oak Ridge National Laboratory

Education:
Ph.D. Computer Science
North Carolina State University

Work:
865.574.8355

Personal:

LinkedIn: linkedin.com/in/sarats

Office: Bldg 4500N, Room F114
Address:
One Bethel Valley Road
Bldg 4500N, MS-6301
Oak Ridge, TN 37831-6301

PGP KeyID: D5F78015