Published papers such as 'Drilling Down I/O Bottlenecks with Cross-layer I/O Profile Exploration' (IPDPS 2024), 'Exploring code portability solutions for HEP with a particle tracking test code' (Frontiers in Big Data, 2024), 'Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels' (CHEP 2023), etc.; Presented doctoral research at SC 2024 Doctoral Showcase.
Research Experience
Collaborated with several U.S. national laboratories including Fermilab, Lawrence Livermore, and Lawrence Berkeley on projects aimed at improving I/O performance in data-intensive HPC and AI/ML applications.
Education
Currently pursuing a Ph.D. at the University of Oregon, co-advised by Dr. Hank Childs and Dr. Allen D. Malony; Received Bachelor's degree in Computer Science from National University of Computer and Emerging Sciences (FAST-NU) in 2018.
Background
A Computer Science Ph.D. Candidate, with research interests in high-performance computing (HPC), performance analysis, parallel I/O, visualization, and systems for AI/ML. Focuses on end-to-end analysis, visualization, and optimization of parallel I/O performance in scientific and AI/ML workloads.
Miscellany
Will be joining Meta as a Ph.D. Software Engineer Intern; Served as a teaching assistant for multiple courses including CS 422: Software Method I, CS 330: C/C++ and Unix, etc.