Hopper Fellow Brings ML, Math, and Algorithmic Expertise to NERSC

Richard Barnes, who first came to Berkeley Lab in 2018 as a research assistant in the Computing Sciences Area and has been a consultant to the Lab since 2020, is the newest Admiral Grace M. Hopper Postdoctoral Fellow. He joined NERSC in November 2021, where he is working on a variety of projects, including bringing HPC to bear in new science areas with novel algorithms, methods, and the use of NERSC’s supercomputing systems. 

Barnes earned his Ph.D. with UC Berkeley’s Energy & Resources Group and Department of Computer Science in 2020. His current research interests include developing and deploying methodological advances in high-performance computing, machine learning, and communication-avoiding algorithms to address analytical challenges in diverse fields of application, often by leveraging graph algorithms.

Over the last 10 years, Barnes has worked with a number of academic institutions, including MIT and the University of Minnesota; national labs, including Berkeley Lab, Brookhaven, Oak Ridge, and NREL; and technology firms, including Facebook, Google, Apple, and NVIDIA. Through these collaborations, he has applied his machine learning and mathematical expertise to a broad spectrum of data challenges, including preventing electoral gerrymandering (MIT), optimizing the use of electric vehicles in public transit systems (Berkeley Lab), enabling the training of massive neural networks (Facebook), accelerating global climate models (U. Minnesota), and improving vehicle routing engines (Apple).

In addition to his Ph.D., Barnes has a master’s in computer science from UC Berkeley and a master’s in ecology from the University of Minnesota, where he also earned a BS in physics and a BA in philosophy. He is also an alumnus of the DOE Computational Science Graduate Fellowship and the Berkeley Institute for Data Science at UC Berkeley.