Koby Hayashi Aims to Emphasize Interpretability with HPC-focused Fellowship
School of Computational Science and Engineering (CSE) first-year Ph.D. student Koby Hayashi won the highly competitive Department of Energy Computational Science Graduate Fellowship (DOE CSGF) for 2019-2020.
Since its establishment in 1991, the DOE CSGF has provided benefits and opportunities to students pursuing doctoral degrees in fields that use high-performance computing (HPC) to solve complex science and engineering problems.
“Many fields at this time are suffering from a number of big data problems. HPC is not exempt from this issue,” said Hayashi. “Through my research, I am aiming to develop tools that alleviate issues for applications that produce data that is too large or too complex to be stored and analyzed with HPC.”
Hayashi’s focus in HPC examines applications in data analysis and emphasizes scalable algorithms and software for the mining, analysis, and compression of data that may be modeled by tensors and hypergraphs.
“Specifically, my focus is on non-negative matrix factorization (NMF) and its variants, tensor factorizations and joint factorizations,” he said. “My goal is to demonstrate the usefulness of these methods combined with developing efficient implementations to allow researchers in various domains to utilize them in their work.”