Ramakrishnan Kannan is the director of Sparsitute. He is Distinguished R&D Staff and the Group Leader for Discrete Algorithms at Oak Ridge National Laboratory. His research expertise is in distributed machine learning and graph algorithms on HPC platforms and their application to scientific data with a focus on accelerating scientific discovery by reducing computation time from weeks to seconds. 

Sherry Li is the deputy director of Sparsitute. She is a Senior Scientist in the Applied Math and Computational Research Division, Lawrence Berkeley National Laboratory. She is the acting depty director for sparsitute project. She has worked on diverse problems in high performance scientific computations, including parallel computing, sparse matrix computations, high precision arithmetic, and combinatorial scientific computing.

David Gleich is a Professor and University Faculty Scholar in the Computer Science Department at Purdue University. His research is on novel models and fast large-scale algorithms for data-driven scientific computing including scientific data analysis, bioinformatics, and network analysis. 

Grey Ballard is an Associate Professor in the Computer Science Department at Wake Forest University. His research interests include numerical linear algebra, high performance computing, and computational science, particularly in developing algorithmic ideas that translate to improved implementations and more efficient software. 

Edgar Solomonik is an Associate Professor in the Computer Science Department at University of Illinois at Urbana-Champaign. His research interests include numerical linear algebra, parallel algorithms, tensor networks, tensor decompositions, high performance computing.

Ariful Azad is an Assistant Professor of Intelligent Systems Engineering (ISE) at Indiana University (IU) School of Informatics, Computing, and Engineering.  His research focuses on parallel graph and sparse matrix algorithms, high performance computing, and their applications in scientific computing and bioinformatics.

Aditya Devarakonda is an Assistant Professor at Wake Forest University. His research interests are at the intersection of high performance computing and machine learning. His research group focuses on deriving s-step numerical optimization algorithms that avoid communication and achieve high performance on distributed-memory parallel systems.

Dmitriy Morozov is a staff scientist in the Machine Learning and Analytics group at the Lawrence Berkeley National Laboratory. His main interests are computational topology and geometry, especially, as they apply to data analysis.

Md Taufique Hussain is a Postdoctoral Fellow in the Department of Computer Science at Wake Forest University. Previously he has been part of Sparsitute as a PhD student at Indiana university. His work touches all three pillars of Sparsitute - matrix, network, and tensor - with large-scale computation as the common thread. During his PhD he worked on sparse matrix kernels with a focus on graph clustering at extreme scale and graph machine learning. During postdoctoral time he extended his work on kernels for large-scale tensor decomposition and random sketching.

Pablo Moriano is a research scientist in the Computer Science and Mathematics Division at Oak Ridge National Laboratory. Dr. Moriano's research lies at the intersection of data science, network science, and cybersecurity. In particular, he uses data-driven and computational methods to discover and understand critical security issues in large-scale networked systems

Piyush Sao is a research scientist in the Discrete Algorithm Group. As part

of his research, he is developing algorithms for high-performance computing systems—such as Oak Ridge National Laboratory’s Summit and Frontier supercomputers—that are used to solve AI and scientific computing problems. 

Oguz Selvitopi is a Research Scientist in the Performance and Algorithms group of Computer Science Department at Lawrence Berkeley National Laboratory. His research interests are high performance computing, parallel sparse matrix computations, combinatorial scientific computing, and bioinformatics. 

Yang Liu is a staff scientist in the Scalable Solvers Group of the Applied Math and Computational Research Division at the Lawrence Berkeley National Laboratory. His main research interest is in numerical linear and multi-linear algebras, computational electromagnetics, computational plasma, scalable machine learning algorithms, and high-performance scientific computing.

Paul Laiu is a Research Staff Mathematician in the Computational and Applied Mathematics (CAM) Group at Oak Ridge National Laboratory. His research interest includes numerical optimization, approximation theory, and numerical schemes for various partial differential equations in kinetic theory.

Caio Alves studied at the Mathematics department of the Federal University of Minas Gerais in Brazil, receiving his PhD in 2014. He went on to postdocs at the University of Campinas, the Max-Planck Institute for Mathematics in the Sciences in Germany, the University of Leipzig, and the Alfred Renyi Institute of Mathematics in Hungary. His field of study is discrete probability, more specifically random graph models, such as percolation models and preferential attachment graphs.

Stefan Schnake is a research scientist in the Multiscale Methods and Dynamics Group at Oak Ridge National Laboratory.  His research interests include sparse-grid and low-rank reduction methods for tensor representations of solutions to dynamical systems

Helen Xu was the 2022 Grace Hopper Postdoctoral Fellow in Computing Sciences at Lawrence Berkeley National Laboratories. Her research interests include parallel computing, cache-efficient algorithms, and performance engineering. She is currently an assistant professor at the School of Computational Science and Engineering of Georgia Tech. 

Arnur Nigmetov is a Computer Systems Engineer at Lawrence Berkeley National Laboratory. 

He received his PhD from the Graz University of Technology (Austria) and first came to LBNL as a postdoc. His research interests are Topological Data Analysis, its applications in Machine Learning, and parallel and distributed computing.

Yuxi Hong is a postdoctoral research fellow in the Performance and Algorithms group of the Computer Science Department at Lawrence Berkeley National Laboratory. He obtained his Ph.D. in Computer Science at King Abdullah University of Science and Technology (KAUST). His current research interests include HPC, Numerical Linear Algebra, GPU programming, sparse computation, low rank methods and efficient Machine Learning/ Deep learning.

Tianyi Shi is a postdoctoral fellow in the Scalable Solvers Group of the Computational Research Division at the Lawrence Berkeley National Laboratory. His main research interest is in numerical linear algebra, including low rank tensor formats and decomposition, randomized algorithms, and sparse solvers. He is also interested in spectral methods for partial differential equations, and high-performance scientific computing.

Yu Zhu is a postdoctoral fellow in the Computer Science Department at Purdue University. Her research interests include higher-order network analysis, network representation learning, graph signal processing, and applications of network science.

Yongseok “Paul” Soh is a Postdoctoral Research Associate in the Discrete Algorithms Group at Oak Ridge National Laboratory. His research focuses on scalable sparse and tensor algorithms, with an emphasis on accelerating irregular workloads such as CP and Tucker factorizations on modern high-performance computing architectures.

Bhisham Dev Verma is a postdoctoral research associate in the Department of Computer Science at Wake Forest University. He received his Ph.D. from the Indian Institute of Technology Mandi. His research interests include randomized dimension reduction, numerical linear algebra, tensor decomposition, and machine learning.

Durga Mandarapu is a postdoctoral research scholar in the Computer Science Department at Lawrence Berkeley National Laboratory. She obtained her Ph.D. in Computer Science at Purdue University. Her current research interests include parallel computing, Ray Tracing architecture, GPU programming, sparse computation, and irregular programs.

David Loiseaux  is a postdoctoral research scholar in the Computer Science Department at Lawrence Berkeley National Laboratory. He received his Ph.D. from Centre Inria d'Université Côte d'Azur in France. His research interests include Topological and Geometrical Data Analysis, and machine learning.

Tong Ding is a Postdoctoral Research Associate in the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign. She received her Ph.D. in Mathematics from Purdue University. Her research interests include numerical linear algebra, tensor computations, and scientific computing.

Navjot Singh is a postdoctoral fellow in the Scalable Solvers Group of the Computational Research Division at the Lawrence Berkeley National Laboratory. His research interests include numerical linear algebra, tensor computations, numerical optimization, and high performance computing.