Naw Safrin Sattar, Ph.D., joined Meharry Medical College as assistant professor of high-performance computing in the Computer Science and Data Science Department in the School of Applied Computational Sciences in July 2025. Dr. Sattar’s research covers high-performance computing, parallel algorithms, scalable large graph mining, big data analytics, and machine learning/deep learning at scale. She seeks to support computational scientists and researchers by developing parallel algorithms to solve computationally expensive problems and achieve optimal performance on exascale HPC systems.
With more than 10 years of experience with HPC, Dr. Sattar’s research focuses on developing scalable parallel algorithms in various application domains. She works on the scalability of neural networks on GPUs, develops prediction machine learning models for scientific domains such as material science, and uses large language models for HPC operational data analytics. She also works on mining and analysis of both static and dynamic large-scale social and information networks by designing parallel algorithms.
Dr. Sattar has worked and collaborated at four Department of Energy national labs: Oak Ridge National Laboratory, Pacific Northwest National Laboratory, Lawrence Berkeley National Laboratory and Los Alamos National Laboratory. These experiences provided her with the opportunity to work on different HPC systems. Collaborating at Berkeley Lab, she developed an optimized distributed parallel algorithm for dynamic graphs, the first MPI-based distributed community detection algorithm for dynamic graphs.
Dr. Sattar was a postdoctoral research associate in the Analytics & AI Methods at Scale group at Oak Ridge National Laboratory. She worked on multiple projects, including Graph500 Benchmark on Frontier Supercomputer, Large Scale Graph Analytics for Heterogeneous Computing Platforms, and Machine Learning assisted HPC Operational Data Analytics. She worked in the National Center for Computational Sciences division at ORNL, which maintains the world’s first exascale supercomputer Frontier and facilitates HPC users and domain scientists enabling HPC in their research.
She established collaboration with Pacific Northwest National Laboratory on the Multi-GPU-based Large-Scale Graph Analytics project and is currently working on applying her developed distributed Multi-GPU algorithm on large protein data. Her collaborative work with PNNL, North Carolina State University, University of Virginia and Washington State University received the ICS’25 Best Paper Award at the ACM International Conference on Supercomputing 2025.
She mentored a post-bachelor’s and a bachelor’s student through DOE-funded internship programs for summer 2023, summer 2024, fall 2024 and spring 2025 semesters, and published several posters and a conference paper based on those internship projects. Throughout her research career, she has published 22 full-length peer-reviewed conference papers and journals, six short papers, and 17 peer-reviewed posters. Her expertise prepared her to integrate research into medical science and higher education with HPC and AI.
Her dissertation focused on distributed graph algorithms and applied machine learning in scientific domains. She has been one of the 15 recipients of the Parallel Computing Summer Research Internship at Los Alamos National Laboratory in Summer 2021. She received the Computing Sciences Research Pathways Fellowship in the student-faculty program from Lawrence Berkeley National Laboratory in Summer 2019. She also received several awards and grants to attend several research conferences and workshops funded by the National Science Foundation and other generous sponsors.
Dr. Sattar serves as a reviewer for journals published by Elsevier, Springer and MDPI. She serves as a technical committee member for ACM and IEEE conferences: Supercomputing, IPDPS, Big Data, ISC and others. She also participates in organizing tutorials and workshops at conferences.