Srinivasan,Ashok_211

Dr. Ashok Srinivasan

Biography:

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 – Bombay, and UCSB, before joining Florida State University, where he was a faculty for 17 years.

Srinivasan’s 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 News, and were listed among 12 major scientific breakthroughs using the Blue Waters supercomputer at the National Center for Supercomputing Applications.

I am interested in artificial intelligence and cognitive science methods and their applications to build a wide range of decision support systems and tools. I am also interested in systems and networks and related security issues. My broad research interests include machine learning, natural language processing, information retrieval, knowledge representation, human-computer interaction, and, more recently, sensor networks and wearable devices.

Current Courses:

  • Parallel Computing

Classes Taught:

    • Advanced Algorithms
    • Advanced Unix Programming
    • Algorithms
    • Analytical Methods in Computer Science
    • Complexity of Algorithms
    • Data Structures
    • GPU Programming
    • Introduction to Computer Science
    • Introduction to Research
    • Introduction to Unix
    • Parallel Computing
    • Theory of Computing

Special Interests:

I am interested in sports, particularly tennis, cricket, and badminton. Another of my favorite hobbies is studying ancient Indian philosophy.

Publications:

    Chunduri, M. Ghaffari, M.S. Lahijani, A. Srinivasan, and S. Namilae. Parallel Low Discrepancy Parameter Sweep for Public Health Policy. Proceedings of the 18th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid), (2018).

    Ghaffari, J. Wang, A. Chari, A. Srinivasan, K. Viswanathan, A. Mubayi, and H. Chi. Integrating Travel and Epidemic Models for Vector Borne Disease Surveillance. 7th International Conference on Innovations in Travel Modeling (ITIM). National Academies – Transportation Research Board. 2018.

    Namilae, A. Srinivasan, A. Mubayi, M. Scotch, and R. Pahle, Self-Propelled Pedestrian Dynamics Model: Application to Passenger Movement and Infection Propagation in Airplanes, Physica A: Statistical Mechanics and its Applications, Vol. 465 (2017) 248-260.

    Derjany, S. Namilae, A. Mubayi, M. Scotch, and A Srinivasan, Multiscale Pedestrian Movement - Infection Dynamics Model for Transportation Hubs. Transportation Research Forum Proceedings, (2017).

    P. Derjany, S. Namilae, A. Mubayi, M. Scotch, and A. SrinivasanMolecular Dynamics Like Numerical Approach for Studying Infection Propagation, Twenty Fifth International conference on composites and nano engineering (ICCE), July (2017).

    Derjany, S. Namilae, A. Mubayi, M. Scotch, and A. Srinivasan. Multiscale model for pedestrian and infection dynamics during air travel, Physical Review E, 95(5) (2017), 052320.

    S. Namilae, A. Srinivasan, C. Sudheer, A. Mubayi, R Pahle, and M. Scotch. Self-Propelled Pedestrian Dynamics Model for Studying Infectious Disease Propagation during Air-Travel. Journal of Transport & Health, 3(2) (2016) S40.

    A. Srinivasan, C.D. Sudheer, and S. Namilae. Optimizing Massively Parallel Simulations of Infection Spread Through Air-Travel for Policy Analysis. Proceedings of the 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid), (2016).


Keywords: Supercomputing, Massively Parallel Computing, High-Performance Computing, GPU Programming, Scientific Computing, Public Policy Analysis, Mathematical Software, Molecular Dynamics, Quantum Monte Carlo, Random Number Generation, Computational Finance, Computational Fluid Dynamics.