Naw Safrin Sattar

Bio

Naw Safrin Sattar is a Postdoctoral Research Associate in the Analytics & AI Methods at Scale group, Advanced Technologies section. Safrin’s research at ORNL will focus on scalability of machine learning models, benchmarking, performance optimization, and large-scale data analytics on HPC systems.

Safrin received her Ph.D. in Computer Science from University of New Orleans (UNO) in August 2022. She joined UNO in Fall 2017 and completed her Master’s in Computer Science in Spring 2019. She obtained her Bachelor’s degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET) in 2016. Her dissertation focused on distributed graph algorithm (particularly community detection) and applied machine learning in scientific domains. Her Ph.D. Dissertation is one of the top 10 dissertations showcased at the leading conference SuperComputing (SC’21). Her research interests include Big Data Analytics, High Performance Computing, Machine / Deep Learning at Scale, Large Graph Mining, Parallel Algorithms, and Performance Optimization. She has been one of the 15 recipients of the Parallel Computing Summer Research Internship at Los Alamos National Laboratory in Summer 2021. She has 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 starting from her undergraduate studies to attend several research conferences and workshops funded by NSF and other generous sponsors. Prior to joining ORNL, she worked as the Graduate Research Assistant in the Big Data and Scalable Computing Research Group during her Ph.D.

Publications