Participants

Rob Ross is the director for RAPIDS. He is a Senior Computer Scientist in the Mathematics and Computer Science Division at Argonne National Laboratory. His interests include the design, implementation, and deployment of complex distributed systems in service of simulation, data, and learning applications in the sciences.

Lenny Oliker is the deputy director for RAPIDS. He is a Senior Computer Scientist in the Computational Research Division at Lawrence Berkeley National Laboratory. His research interests include optimization of scientific methods, performance evaluation, autotuning, domain-optimized computational architectures, and large-scale genome assembly.

Scott Klasky is the ORNL PI, and the Application Engagement lead for RAPIDS. He is a Distinguished R&D Staff Member and the group leader of the Scientific Data Group at Oak Ridge National Laboratory. More information on his R&D contributions can be found on his google scholar page.

 Khaled Ibrahim is the Application Engagement co-lead for RAPIDS.  He is a Computer Scientist in the Computational Research Division at Lawrence Berkeley National Laboratory. His research interests include performance modeling, analysis and tuning. He also conducts research in communication runtime optimization. 

Shinjae Yoo is the AI/ML lead for RAPIDS. He works on various aspects of AI/ML from a foundational theory to scalable machine learning models on scientific frontier applications. More information is available at http://sjyoo.com.

Sandeep Madireddy  is the is the AI/ML co-lead. He is an Assistant Computer Scientist at Argonne National Laboratory. His research interests include theoretical and applied machine learning, probabilistic modeling and HPC. He has experience applying them to diverse problems in various domains, ranging from physical sciences to computer systems modeling and neuromorphic computing. For more information see http://www.mcs.anl.gov/~smadireddy/ 

Sam Williams is the Performance, Energy, and Proxy Applications lead for RAPIDS. He is a Senior Staff Scientist in the Computational Research Division at the Lawrence Berkeley National Laboratory. His research interests include performance optimization, performance modeling, computer architecture, and high-performance, scalable linear solvers. 

Xingfu Wu is the Performance, Energy, and Proxy Applications co-lead . He is a staff scientist at Argonne National Laboratory and a CASE senior scientist at the University of Chicago. His research interests include performance analysis and modeling, performane optimization, autotuning, energy efficient computing, power modeling, and machine learning.  

Rob Latham is the Scientific Data Management lead for RAPIDS. He is Principle Software Development Specialist at Argonne National Laboratory and works on high performance IO libraries and tools for scientific applications.

Ana Gainaru is the Scientific Data Management lead for RAPIDS. She is a Computer Scientist in the Workflow group at Oak Ridge National Laboratory. Her research interest includes workflow and data management for large-scale complex applications that combine traditional HPC with AI/ML.

Berk Geveci is the Software Stewardship lead for RAPIDS. He also leads the Scientific Computing team at Kitware Inc. He is one of the leading developers of the ParaView visualization application and the Visualization Toolkit (VTK). His research interests include large scale parallel computing, computational dynamics, finite elements & visualization algorithms.

Tanwi Mallick is a computer scientist in the Mathematics and Computer Science Division at Argonne National Laboratory. Her research is primarily focused on spatiotemporal graph neural networks, uncertainty quantification, trustworthy scientific machine learning (SciML), foundation models, LLM Agents, and high-performance computing.

Aditi Krishnapriyan is a faculty member at UC Berkeley in EECS and Chemical Engineering departments, a member of Berkeley AI Research (BAIR), and a faculty scientist at Lawrence Berkeley National Laboratory. Her research interests include physics-inspired machine learning methods; geometric deep learning; inverse problems; and the development of machine learning methods informed by physical sciences applications including molecular and fluid dynamics. More information is available at https://a1k12.github.io/.

Wei-keng Liao is a Research Professor in the Department of Electrical Engineering and Computer Science at the Northwestern University. His research interests include parallel and distributed file I/O and storage system, high-performance data mining algorithm design, and software development for Parallel NetCDF.

Seyong Lee is a Senior R&D Staff Member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory. His research interests include parallel programming and performance optimization in heterogeneous computing environments, program analysis, and optimizing compilers. See his website for more information: https://seyonglee.github.io. 

Paul Hovland is a Senior Computer Scientist in the Mathematics and Computer Science Division at Argonne National Laboratory. His research focuses on software engineering for high performance scientific applications; areas of interest include automatic differentiation, domain specific languages, and performance engineering.

Kshitij Mehta is a computer scientist in the Workflow Systems Group at Oak Ridge National Laboratory. His research interests include scalable workflow automation and management of large scientific data.

Hanqi Guo is with the Department of Computer Science and Engineering at The Ohio State University. His research interests include data analysis, visualization, and machine learning for scientific data.

Anshu Dubey is a Computational Scientist at Argonne National Laboratory, and a Senior Scientist for CASE in the Computer Science Department, University of Chicago. Her research interests include multiphysics scientific software, adaptive mesh refinement and software sustainability for scientific software.

Prasanna Balaprakash is the Director of AI Programs and Distinguished R&D Scientist at Oak Ridge National Laboratory. His research interests span artificial intelligence, machine learning, optimization, and high-performance computing. For more information see https://pbalapra.github.io/ 

Qian Gong is a  R&D Staff Member in the Workflow System Group at Oak Ridge National Laboratory. She has been leading the development of the MGARD reduction framework.Her research focuses on scalable in situ and file system I/O.

David Pugmire is the Data Understanding co-lead for RAPIDS. He is a Distinguished R&D Staff Member and Visualization Team Lead in the Scientific Data Group at Oak Ridge National Laboratory. His research focuses on scalable in situ visualization and analysis on HPC systems.

Wei Xu is a Computer Scientist in Computational Science Initiative at Brookhaven National Laboratory, and a Research Assistant Professor in Computer Science Department at Stony Brook University. Her research interests are visual analytics and machine learning. More information is available at: https://sites.google.com/site/weixusbu2012

Xihaier Luo is a staff member at Brookhaven National Laboratory. His research interests lie at the intersection of machine learning and scientific computing. For more information see: https://xihaier.github.io/ 

Yihui (Ray) Ren is a Computational Scientist in the AI Department, Computing and Data Science directorate at Brookhaven National Laboratory. His  research interests include developing foundation models for scientific applications, Agentic AI, AI Codesign for high performance computing and edge environments and brain-inspired neuromorphic computing.

Dmitriy Morozov is a research scientist in the Data Analytics and Visualization group at Lawrence Berkeley National Laboratory. His research interests include computational geometry, topology, and high-performance computing.

Krishnan Raghavan is a Postdoctoral Fellow at Argonne National Laboratory. His current research interests include continual learning, reinforcement learning, graph theory, spatio-temporal statistics and control.

Arnur Nigmetov is a Computer Systems Engineer at Lawrence Berkeley National Laboratory. His research interests include topological data analysis, scientific machine learning, and parallel and distributed algorithms. 

Kenneth Moreland is a Senior Research Scientist at Oak Ridge National Laboratory for the Visualization group in the Computer Science and Mathematics Division. His research interests include large-scale visualization and visualization algorithms for multi-core, many-core, and future-generation computer hardware. More information is available at https://www.kennethmoreland.com/. 

Jan Hückelheim is an Assistant Computer Scientist at Argonne National Laboratory. He is interested in program analysis and transformation techniques, including automatic differentiation and formal verification, particularly for programs running on multi-core and many-core machines.

Zhe Bai is a computational science researcher in the Applied Mathematics and Computational Research Division at Lawrence Berkeley National Laboratory. Her interests include reduced order modeling, scientific machine learning, and dynamical system identification with control.

Norbert Podhorszki is a Distinguished R&D Staff Member in the Workflow System Group at Oak Ridge National Laboratory. He has been leading the development of the ADIOS I/O framework His research focuses on scalable in situ and file system I/O

Christopher Kelly is a research scientist in the Computational Science Department and leader of the Scientific Computing Applications Group at Brookhaven National Laboratory. His research interests include Lattice QCD, high-performance computing, performance analysis and machine learning. He is the lead backend developer of the Chimbuko performance analysis tool and the maintainer of ExaRL.

Orcun Yildiz is a principal software development specialist with the Mathematics and Computer Science Division at Argonne National Laboratory. His research interests include scientific workflows, I/O management, and convergence of HPC, AI, and Big Data processing.

Romain Egele is a computer scientist in the Workflow System Group at Oak Ridge National Laboratory. He has been leading the development of DeepHyper. His research focus is on Machine Learning (Optimization and Uncertainty Quantification).

Sanket Jantre  is a computational scientist in the Applied Mathematics department within the Computing and Data Sciences directorate at Brookhaven National Laboratory. His research interests include Bayesian machine learning, dimensionality reduction, and surrogate modeling.

Jean Luca Bez is a Research Scientist at Lawrence Berkeley National Laboratory. His work broadly addresses data management challenges in HPC and AI, the optimization of I/O performance for large-scale scientific applications, automatic tuning, and novel storage solutions to manage data at exascale.

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