Mahantesh Halappanavar is the lead PI of the ExaGraph co-design center. He is a Senior Research Scientist in the Advanced Computing, Mathematics, and Data Division at the Pacific Northwest National Laboratory. He is a member of the Data Sciences Group and leads the Data Analytics team. His research interests broadly include parallel graph algorithms, data intensive computing, scientific computing, high-performance computing, and machine learning.
Aydin Buluc is a Staff Scientist at the Lawrence Berkeley National Lab and a Adjunct Assistant Professor of Electrical Engineering and Computer Sciences at UC Berkeley. His research focuses on high-performance graph analysis and libraries, parallel sparse matrix computations, communication-avoiding algorithms, with applications in computational genomics and machine learning.
Alex Pothen is a Professor of Computer Science at Purdue University. His research focuses on combinatorial scientific computing, parallel graph algorithms, and applications in bioinformatics and computational biology.
Erik Boman is a scientist at Sandia National Labs. He works in the Scalable Algorithms group in the Center for Computing Research. His research areas include high-performance computing, combinatorial scientific computing, sparse matrix computations and numerical linear algebra. He serves on the editorial board of several journals, including SIAM J. Sci. Comp. and ACM TOMS.
Ariful Azad is an Assistant Professor of Intelligent Systems Engineering at Indiana University, Bloomington. His research focuses on parallel graph algorithms, sparse matrix computations, high-performance computing and applications in computational biology and scientific computing.
Antonino Tumeo is a Senior Research Scientist in the High Performance Computing Group at Pacific Northwest National Laboratory. His research interests are modeling and simulation of high performance architectures, hardware-software codesign, FPGA prototyping and GPGPU computing, with a focus on irregular workloads.
Arif Khan is a Scientist at Pacific Northwest National Laboratory. His research interest includes graph algorithm, high performance computing, approximation algorithm along with their applications in bioinformatics, scientific computing and machine learning.
Saliya Ekanayake is a Postdoctoral Scholar in the Performance and Algorithms Research (PAR) group at Lawrence Berkeley National Laboratory. He is broadly interested in Big Data, machine learning, and parallel programming.
Sayan Ghosh is a PhD student at Washington State University in Pullman, WA and, an Alternate Sponsored Fellow (ASF) at Pacific Northwest National Laboratory. He is broadly interested in applying one-sided communication models in building scientific applications.