2026 Winners

Tanzima Z. Islam

Tanzima is an Associate Professor of Computer Science and Director of the Per4ML Laboratory at Texas State University. She also holds a dual appointment as an Associate Computational Scientist in the AI Department within Brookhaven National Laboratory's Computing and Data Sciences Directorate. Her research spans high-performance computing, performance analysis, machine learning, resilience, and data-driven decision-making for increasingly complex, heterogeneous systems.

Her early work on scalable checkpoint/restart shaped techniques was later incorporated into LLNL's Scalable Checkpoint/Restart (SCR) framework, an R&D 100 Award winner in 2019. Her more recent research has pioneered machine-learning approaches to performance characterization and prediction across heterogeneous platforms, from interpretable performance analysis to generative-AI methods for performance optimization. This work has attracted more than $5.25 million in external funding, including a DOE Early Career Research Program Award, an NSF CAREER Award, and a 2026 DOE Genesis Mission Phase 1 Award for Optix, her multimodal foundation model for performance-aware HPC code intelligence.

Tanzima's influence extends well beyond her own research output. The research and mentoring platform she co-founded, Bangladeshi Women in Computer Science and Engineering (BWCSE), has supported hundreds of women pursuing graduate education, research opportunities, fellowships, and careers in computing in Bangladesh and abroad. She has also built hands-on training programs for the next generation of HPC software researchers and taken on leadership roles across the field's major conferences, including SC, IPDPS, HPDC, ISC, ICPP, and CCGrid. Through her mentorship, service, and close ties to the national laboratories, she has become a vital link between academic research and the practical needs of leadership-class computing facilities.

Olga Pearce

Olga is a Computer Scientist and Principal Member of Technical Staff in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. She also holds a joint appointment as an Associate Professor of Practice at Texas A&M University.  Her work encompasses scientific simulation, parallel algorithms and programming models, performance modeling and optimization, system software, HPC architectures, and reproducible, continuous benchmarking.

Olga's contributions have reshaped how leadership-class systems are evaluated and understood. At LLNL, she has led benchmarking for the procurement and acceptance of Advanced Technology Systems, including El Capitan, and directs development of Benchpark, an open, collaborative repository for reproducible HPC benchmark specifications that enables continuous benchmarking across systems. She also leads Thicket, an open-source framework for exploratory analysis of performance data across experiments, architectures, and tools, and previously led Hatchet, a scalable, call-tree-based performance analysis tool. Olga’s broader portfolio includes work on Caliper, the RAJA performance-portability ecosystem, load balancing, heterogeneous architectures, and performance analysis for large-scale multiphysics simulations.  LLNL heavily leverages her expertise in multiphysics simulations and performance analysis to understand current and future HPC workloads and system requirements, and to communicate with hardware vendors and external entities such as the National Academies of Sciences.  

The reach of that work is evident in some of the nation's most advanced computing systems. Olga has been recognized by LLNL for leading benchmarking on the acceptance of both the Early Access System for El Capitan and El Capitan itself, as well as for developing GPU capabilities for the MARBL multiphysics code, advancing the RAJA performance-portability model, and optimizing applications for LLNL's accelerated computing systems. Across this work, she has bridged fundamental HPC research and production deployment, giving developers and facilities reliable ways to measure performance across rapidly evolving architectures.

Olga has also shaped the community around her field. She has co-chaired the Salishan Conference on High Speed Computing since 2019, contributed extensively to SC, IPDPS, PASC, ICPP, and ISC, and mentored graduate students across performance analysis, visualization, programming models, compilers, and the convergence of HPC and cloud computing. As a graduate student, she helped start the Student Cluster Challenge at SC|07, the competition which introduces undergraduate students to real world HPC challenges and has grown to multiple tracks at SC in the United States, ISC in Europe, and ASC in Asia.  As an Associate Professor of Practice at Texas A&M University, she has also brought her national-laboratory experience directly into the classroom, teaching parallel computing to hundreds of students.

"Tanzima and Olga exemplify the spirit of this award through two different but equally compelling paths of technical leadership," said Michela Taufer, MathWorks Professor at the University of Tennessee, Knoxville, and Chair of the SIGHPC Emerging Woman Leader in Technical Computing Award Committee. "Tanzima combines sustained technical excellence with an extraordinary commitment to mentoring, education, and community building, while Olga's transformative contributions to HPC software and benchmarking have delivered tools and capabilities with lasting impact on national missions and the broader HPC ecosystem. They demonstrate the many ways emerging leaders can shape the future of high-performance computing."