麻豆传媒

Dr. Ashok Srinivasan is the William Nystul Eminent Scholar Chair and Professor. He obtained his Ph.D. in Computer Science from the University of California, Santa Barbara, with a dissertation on Computational Issues in the Solution of Liquid Crystalline Polymer Flow Problems. He then performed postdoctoral research at the University of Illinois at Urbana-Champaign, where he developed the SPRNG parallel random number generation software, which is used by major research groups around the world. He subsequently worked at the Indian Institute of Technology 鈥� Bombay, and UCSB, before joining Florida State University, where he was a faculty for 17 years.

Srinivasan鈥檚 research has been widely recognized. He was a Fulbright Senior Research Scholar and has received Best Paper awards at multiple international conferences, including the International Conference on Parallel Processing (ICPP). He has given around 30 invited talks in universities and labs in the USA and abroad, such as at the University of California, San Diego, and Oak Ridge National Lab. He has been PI or co-PI on research grants for around $ 4 million from the National Science Foundation, Department of Energy, Department of Defense, etc. He has reviewed proposals for the National Academies, National Science Foundation, National Institutes for Health, and the Fulbright program.

Srinivasan is keen on fostering student research and in service to the professional community. He is a founding co-chair of the Student Research Symposium at the IEEE/ACM International Conference on High-Performance Computing, Data, and Analytics (HiPC). He has organized around 15 professional events and has served on technical program committees for over 40 international conferences, including SC and IPDPS. He has collaborated with researchers in industry and national labs, such as at IBM and Argonne National Lab, and has been involved in interdisciplinary activities with experts from a variety of fields, such as biochemistry, bioinformatics, chemical engineering, epidemiology, finance, materials, mathematics, mechanical engineering, physics, and urban planning. Further details on his work are available at http://www.cs.fsu.edu/~asriniva.

Degrees & Institutions:
Ph.D. Computer Science, University of California, Santa Barbara, 1996.
M.S. Polymer Engineering, University of Akron, 1992.
B.S. Tech (Honours) Chemical Engineering, Regional Engineering College, Tiruchirapalli, 1987.

Research:
My research expertise lies in high-performance computing, with a focus on applications of supercomputing to science and public policy. I lead Project VIPRA (www.cs.fsu.edu/vipra), which is a multi-university effort for simulation-based analysis of public policy options to reduce the likelihood of infection spread through air travel. Our results have been reported in over 75 news outlets around the world, such as Economist and Fox 麻豆传媒, and were listed among 12 major scientific breakthroughs using the Blue Waters supercomputer at the National Center for Supercomputing Applications.

Satish Karra is a computational scientist with the Systems Modeling and Computational Science team. He joined EMSL in 2022 as the lead scientist for the . In this role, he oversees the computational resource needs of EMSL users and advises on simulation and computational strategies to achieve their science objectives. He co-leads road mapping for EMSL's computing and modeling vision.
Satish has 15 years of experience developing scientific software products (high-performance computing, machine learning) for various DOE and private sponsors. Satish’s research is at the interface of engineering, geoscience, applied mathematics, and computing, to solve real-world problems in energy and environmental sciences. He is an expert in building coupled multi-physics and multi-scale models for subsurface applications. His recent works build reduced-order approaches using machine learning and graph-based techniques that emulate physics towards faster decision-making. He also develops methods to link models and experimental data via machine learning. He has 75+ peer-reviewed journal papers and book chapters and is a reviewer for a broad range of journals in computational science, geoscience, flow and transport, and mechanics. He is a developer of the massively parallel code  and led the parallelization effort in the R&D100 award-winning suite . Satish has mentored 20 students and postdocs. Before joining EMSL, Satish was the team leader for the Subsurface Flow and Transport Team at LANL. At LANL, he led and contributed to projects in the areas of energy, global security, and nuclear security.

Research Interests


Porous media modeling
Reduced-order modeling
Multi-physics and multi-scale coupling
Physics-informed machine learning


Education


PhD in Mechanical Engineering, Texas A&M University (2011)
MS in Mechanical Engineering, Texas A&M University (2007)
BTech in Mechanical Engineering, Indian Institute of Technology Madras (2005)


Awards and Recognition


LANL SPOT awards for team leadership and positive influence on co-workers, 2020, 2021.
Distinguished Performance Award (Subsurface Hydrology, Geology, and Geochemistry Science Team), Los Alamos National Laboratory, 2019.
Los Alamos Awards Program award for Publication, Los Alamos National Laboratory, 2017 & 2019.
Distinguished Performance Award (dfnWorks Team), Los Alamos National Laboratory, 2018.
R&D100 Award for dfnWorks, 2017.
Federal Laboratory Consortium for Technology Transfer Notable Technology Development Award for dfnWorks Software Suite, 2017.
Los Alamos Awards Program award for Outstanding Performance in Prototyping Three-dimensional Calculations and Visualizing of Gas Migration in Fractures Following a Subsurface Explosion, Los Alamos National Laboratory, 2016.
Los Alamos LDRD Early Career Award, Los Alamos National Laboratory, 2014.
Outstanding Graduate Student Teaching Award, Texas A&M University, 2010.
Mechanical Engineering Graduate Fellowship, Texas A&M University, 2005-06.
‘Graduate Pool’ Fellowship, Texas A&M University, 2005-06.