Dilma Da Silva is a Regents Professor and holder of the Ford Design Professorship II in the Department of Computer Science and Engineering at Texas A&M University. From July 2022 to June 2026, she served in several leadership positions at the U.S. National Science Foundation. Her roles at Texas A&M include Department Head (2014-2019), Associate Dean (2019-2020), interim Director of the Texas A&M Institute of Data Science, and interim Director of the Texas A&M Cybersecurity Center. Her primary research interests are high performance computing, computer science education, and quantum computing. Before joining Texas A&M, she worked at Qualcomm Research (2012-2014), IBM Research (2000-2012), and the University of São Paulo (1996-2000). Dilma is an ACM Distinguished Scientist. She is passionate about mentoring and supporting the next generation of computing researchers and practitioners.

Peter Dinda is a professor in the Department of Computer Science at Northwestern University and also holds an appointment in the Department of Electrical and Computer Engineering. He works in experimental computer systems, particularly parallel and distributed systems, and has authored over 140 scientific papers, authored or is a major contributor to several large publicly available codebases, and holds five patents. His research currently involves virtualization and operating systems for distributed and parallel computing, programming languages for parallel computing, and empathic systems for bridging individual user satisfaction and systems-level decision-making. He is a Fellow of the IEEE. You can find out more about him at pdinda.org.

Jay Lofstead is a Principal Member of Technical Staff in the Scalable System Software department of the Center for Computing Research at Sandia National Laboratories in Albuquerque, NM. His work focuses on infrastructure to support all varieties of simulation, scientific, and engineering workflows with a strong emphasis on IO, middleware, storage, transactions, operating system features to support workflows, containers, software engineering and reproducibility. He is co-founder of the IO-500 storage list. He also works extensively to support various student mentoring and diversity programs at several venues each year, including outreach to both high school and college students. Jay was a recipient of a 2013 R&D 100 award for his work on the ADIOS IO library.

Sarah Neuwirth is a tenured Professor of Computer Science at Johannes Gutenberg University Mainz (JGU), Germany. She is also responsible for the management and further development of JGU's High Performance Computing division, the coordination of HPC activities at regional and national levels, and the representation of JGU in the committees of the NHR, the NHR South-West, and the Gauss-Allianz. She is a Visiting Researcher at the Jülich Supercomputing Center, Germany. Her research interests include parallel file and storage systems, modular supercomputing (i.e., resource disaggregation and virtualization), performance engineering, high-performance computing and networking, reproducible benchmarking, parallel I/O, and parallel programming models. She has been awarded the "2023 PRACE Ada Lovelace Award for HPC" and the "ZONTA Science Award 2019".

Douglas Thain is a Professor in the Department of Computer Science and Engineering at the University of Notre Dame. He directs the Cooperative Computing Lab at Notre Dame, which focuses on the design of large-scale distributed computing systems for grand-challenge problems in science and engineering. His team is active in publishing open-source software systems such as Floability, TaskVine Makeflow, Parrot, and others. Dr. Thain has received multiple teaching awards at Notre Dame for his courses in distributed systems, operating systems, and compilers, and has published an introductory textbook on compilers (compilerbook.org), an open-source operating system kernel (Basekernel), and an online course in Data-Intensive Scientific Computing (DISC).

Hariharan Devarajan is a Computer Scientist in the Parallel Systems Group within the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory, where he has been conducting research since 2021. His work focuses on data management, storage systems, and scalable performance analysis for extreme-scale HPC and AI workloads. His research spans the entire data stack, from understanding application I/O requirements through frameworks such as Mimir and H5Intent, to developing performance monitoring and explainability tools including DFTracer and DataCrumbs, large-scale analysis systems such as WisIO and Horatio, storage middleware including Hermes, UnifyFS, and the Scalable Checkpoint/Restart (SCR) library, and benchmarking frameworks such as the DLIO Benchmark for evaluating next-generation HPC storage systems. Hariharan currently serves as Co-Principal Investigator of the Deep Learning Data Loading (DLDL) LDRD project, where he is developing workload-aware data management techniques for distributed AI applications. He has also led I/O research within the FRACTALE project, advancing data-aware scheduling and storage optimization for large-scale scientific workflows. His research brings together application characterization, systems software, storage architecture, and large-scale experimental evaluation to build the next generation of intelligent HPC storage systems. He has received Best Paper Awards at HPDC and CCGrid and is an active member of the HPC community, serving in leadership roles for conferences including HPDC, Cluster, and SSDBM.

Michael E. Papka is an Argonne Distinguished Fellow and Senior Scientist at Argonne National Laboratory, where he serves as deputy associate laboratory director for Computing, Environment and Life Sciences and director of the Argonne Leadership Computing Facility, a U.S. Department of Energy Office of Science user facility. He is also the Warren S. McCulloch Professor of Computer Science and director of the Electronic Visualization Laboratory at the University of Illinois Chicago. His research focuses on the convergence of high-performance computing, artificial intelligence, data-intensive computing, and visualization to accelerate scientific discovery. As leader of one of the world's largest open-science computing facilities, he works at the forefront of emerging computing architectures, from leadership-class supercomputers to AI-driven systems, helping researchers address challenges in energy, climate, biology, materials science, and other data-intensive domains. His experience spans the evolution of large-scale computing infrastructure and its role in advancing both scientific research and AI-enabled discovery. Dr. Papka holds degrees in computer science and physics from the University of Chicago, the University of Illinois Chicago, and Northern Illinois University.

Osamu Tatebe received his Ph.D. in Computer Science from the University of Tokyo in 1997. He worked at the Electrotechnical Laboratory (ETL) and the National Institute of Advanced Industrial Science and Technology (AIST) until 2006. He is currently a professor at the Center for Computational Sciences at the University of Tsukuba. Since 2000, he has led the research and development of the Gfarm file system, which is currently used in a nationwide 100PB HPCI shared storage infrastructure in Japan. He is presently engaged in the exploration of the next generation of high performance computing (HPC) storage architecture. He has received awards in the SC2003 High Performance Bandwidth Challenge, the SC2005 StorCloud Challenge, and the SC2006 Storage Challenge. His research interests include HPC storage architecture and HPC system software.

Michela Taufer is the MathWorks Professor at the University of Tennessee, Knoxville. She is an ACM Distinguished Scientist, an IEEE Senior Member, a Fellow of the American Association for the Advancement of Science (AAAS), a member of the Board of Directors of the Computing Research Association (CRA), and a member of the Computing Community Consortium (CCC). She received the 2025 IEEE/ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC) Achievement Award. Her research spans high-performance computing, cloud computing, and artificial intelligence and machine learning (AI/ML), with a focus on reproducible, scalable, and transparent scientific computing. She has made pioneering contributions to volunteer computing, accelerator-based supercomputing, performance portability, and FAIR (Findable, Accessible, Interoperable, and Reusable) data frameworks, including the National Science Data Fabric (NSDF). Taufer leads interdisciplinary collaborations among universities, U.S. national laboratories, and industry partners to advance AI-enabled scientific discovery, workflow automation, and sustainable cyberinfrastructure. Her work has advanced scientific data management, reproducible computing, and autonomous workflows for data-intensive science.

Karen Tomko serves as Director of Research Software Applications and Manager of the Scientific Applications group at the Ohio Supercomputer Center. She has been working in the high-performance computing field for more than 25 years and has research software engineering experience with a wide range of applications in engineering, physics and earth sciences. Her research interests include communication runtimes, AI for research, AI infrastructure and research software engineering. Tomko is also focused on workforce development of research cyberinfrastructure professionals and expanding AI expertise within the community. Prior to joining OSC, Tomko held faculty appointments in computer science and engineering at the University of Cincinnati and Wright State University. Tomko earned a doctorate and a master's degree in computer science and engineering from the University of Michigan.