He will join the Mathematics and Computer Science (MCS) division in September, where he will be developing constrained low-rank approximation (CLRA) methods for scalable data analysis.
“I am excited to have the opportunity to work at Argonne and participate in its world-class research,” Eswar said. “The machine learning projects in MCS especially resonate with my interest in integrating machine learning techniques with high-performance computing to develop efficient data analytics workflows.”
Eswar is currently completing his Ph.D. in computer science from the Georgia Institute of Technology. His work was recognized by an NSF INTERN fellowship in 2020. Moreover, he has already coauthored papers in 8 peer-reviewed journals and international conferences, including the ACM Transactions on Mathematical Software in 2021 and the SC supercomputing conference in 2020. The CLRA techniques Eswar plans to work on with MCS division researchers can help guide scientists in choosing among myriad options in a pipeline and can help automate part of the experimentation process.
The appointment as Wilkinson Fellow lasts a year and can be extended an additional year. Benefits include salary, moving expenses, and a professional travel allowance.