Inderjit S Dhillon
Gottesman Family Centennial Professor
University of Texas at Austin
Department of Computer Science
Austin, TX, USA
He is an ACM Fellow, IEEE Fellow, SIAM Fellow, AAAS Fellow and has won the SIAM Linear Algebra Prize. His research interests are in machine learning, large-scale data analysis and bioinformatics. His emphasis is on developing novel algorithms that respect the underlying problem structure and are scalable to massive data sets. Some of his current research topics: high-dimensional data analysis, divide-and-conquer methods for big data analytics, social network analysis, and predicting gene-disease associations.
David A. Bader
Chair, School of Computational Science and Engineering
Executive Director of High Performance Computing
College of Computing
Georgia Institute of Technology, Atlanta
He received his Ph.D. in 1996 from The University of Maryland, and his research is supported through highly-competitive research awards, primarily from NSF, NIH, DARPA, and DOE. Dr. Bader serves as a board member of the Computing Research Association (CRA), on the NSF Advisory Committee on Cyberinfrastructure, on the Council on Competitiveness High Performance Computing Advisory Committee, on the IEEE Computer Society Board of Governors, and on the Steering Committees of the IPDPS and HiPC conferences. He is the editor-in-chief of IEEE Transactions on Parallel and Distributed Systems (TPDS) and Program Chair for IPDPS 2014. Bader also serves as an associate editor for several high impact publications including IEEE Transactions on Computers (TC), ACM Transactions on Parallel Computing (TOPC), and ACM Journal of Experimental Algorithmics (JEA).
Dr. Bader‘s interests are at the intersection of high-performance computing and real-world applications, including computational biology and genomics and massive-scale data analytics. He has co-chaired a series of meetings, the IEEE International Workshop on High-Performance Computational Biology (HiCOMB), co-organized the NSF Workshop on Petascale Computing in the Biological Sciences, written several book chapters, and co-edited special issues of the Journal of Parallel and Distributed Computing (JPDC) and IEEE TPDS on high-performance computational biology. He is also a leading expert on multicore, manycore, and multithreaded computing for data-intensive applications such as those in massive-scale graph analytics. His main areas of research are in parallel algorithms, combinatorial optimization, massive-scale social networks, and computational biology and genomics.
Prof. Bader is a Fellow of the IEEE and AAAS, a National Science Foundation CAREER Award recipient, and has received numerous industrial awards from IBM, NVIDIA, Intel, Cray, Oracle/Sun Microsystems, and Microsoft Research. Dr. Bader has served as a lead scientist in several DARPA programs including High Productivity Computing Systems (HPCS) with IBM PERCS, Ubiquitous High Performance Computing (UHPC) with NVIDIA ECHELON, Anomaly Detection at Multiple Scales (ADAMS) and Power Efficiency Revolution For Embedded Computing Technologies (PERFECT). He has also served as Director of the Sony-Toshiba-IBM Center of Competence for the Cell Broadband Engine Processor. Bader is a co-founder of the Graph500 List for benchmarking “Big Data” computing platforms. Bader is recognized as a “RockStar” of High Performance Computing by InsideHPC and as HPCwire‘s People to Watch in 2012 and 2014.
Senior Scientist ST for Advanced Computing Concepts
Current : U.S. Naval Research Laboratory
Previous : Air Force Research Laboratory, IEEE Mohawk Valley Section, Air Force Institute of Technology
Education : University of Miami
Senior Scientific Professional member of the SES Cadre, accomplished technical-leader with a track record of research, technology transition, interagency collaborations, program creation and execution, mentoring, scholarly publications, tenured professorship and professional recognition – as an IEEE Fellow – for contributions to high performance computer vision algorithms for airborne applications. Specialties: Computer vision; wide area imaging; video (FMV) exploitation; autonomy; cyber security; information fusion; machine learning; persistent surveillance; autonomous vehicles; self geo-localization; multi-core heterogeneous computing methods; and, high performance computing in embedded systems. http: //www.cacs.louisiana.edu/~guna and http://cell.missouri.edu/people/14/
Honors & Awards
The Board of Directors, Institute for Electrical and Electronics Engineers November 2014
Recognized for contributions to high-performance computer vision algorithms for airborne applications.
The IEEE Grade of Fellow is conferred by the IEEE Board of Directors upon a person with an extraordinary record of accomplishments in any of the IEEE fields of interest. If you would like to learn more about IEEE or the IEEE Fellow Program, please visit http://www.ieee.org/fellows.
P. (Saday) Sadayappan
Department of Computer Science and Engineering
595 Dreese Lab, 2015 Neil Avenue
Ohio State University, Columbus, Ohio 43210 USA
+1-614-292-0053 (office), +1-614-292-2911 (fax)
- CSE 5441 (Introducton to Parallel Computing)
- CSE 6441 (Parallel Computing)
- Compiler Optimization for High Performance Computing
- Domain-Specific Compile/Runtime Optimization
- Data Movement Complexity of Computations
- Tensor Contraction Engine (TCE)
- Polyhedral Compiler Optimization
- EAGER: Towards Automated Characterization of the Data-Movement Complexity of Large Scale Analytics Applications, NSF, 2016-2019.
- XPS: FULL: Collaborative Research: PARAGRAPH: Parallel, Scalable Graph Analytics, NSF, 2016-2019.
- Whole-Program Adaptive Error Detection and Mitigation, DOE, 2015-2018 (Project PI: Sriram Krishnamoorthy, PNNL).
- Improving Vectorization, NSF, 2014-2017.
- Compiler/Runtime Support for Developing Scalable Parallel Multi-Scale Multi-Physics Applications, NSF, 2014-2017.
- Characterization of bandwidth requirements of algorithms for extreme scale science, DOE, 2014-2016.
- Domain Specific Language Support for Exascale, DOE, 2013-2016 (Project PI: Daniel Quinlan, LLNL).
- Large-Scale Computation of the Phonon Boltzmann Transport Equation, NSF, 2012-2016 (PI: Sandip Mazumder).
- A Polyhedral Transformation Framework for Compiler Optimizations, DOE, 2010-2014.
- An environment for high-productivity high-performance computing using GPUs/Accelerators, NSF, 2009-2013.
- Global graphs: A middleware for data intensive computing, NSF, 2009-2013 (PI: Srinivasan Parthasarathy).
- Petascale simulations of quantum systems by stochastic methods, NSF, 2009-2013 (Project PI: David Ceperley, Univ. Illinois).
- Customizable domain-specific computing, NSF, 2009-2014 (Project PI: Jason Cong, UCLA).