Kevin A. Brown

Kevin A. Brown serves as an Assistant Computer Scientist and the inaugural Walter Massey Fellow at Argonne National Laboratory, where he conducts research in the Mathematics and Computer Science Division. His work focuses on network performance analysis and simulation, with particular emphasis on accelerating parallel discrete event simulations using surrogate models and improving resilience of geographically-distributed research infrastructure.

Dr. Brown received his Ph.D. and M.Sc. in Mathematical and Computing Sciences from Tokyo Institute of Technology in 2018 and 2014 respectively, and his B.Sc. in Computing and Information Technology from the University of Technology, Jamaica in 2008.

His research interests span network performance measurement, analysis, and visualization; network interconnects design and simulation; parallel I/O and storage; and communication optimization. His current work as Principal Investigator for the LDRD-funded project "Improving Data Movement Performance for Emerging AI and Climate Science Workloads on Future Supercomputers" demonstrates his leadership in applying machine learning to configure network quality-of-service for next-generation supercomputing applications.

His publication record shows consistent contributions to high-performance computing conferences, with a focus on network performance analysis and optimization for fat-tree architectures. His work bridges theoretical network models with practical implementations for exascale systems.

• Japanese Government (Monbukagakusho: MEXT) Scholarships (2012-2017)
• Nominee - Prime Minister's Youth Award for Excellence (2010)
• UTech, Ja. Foundation Scholarship (2005-2008)

Dr. Brown's career trajectory includes significant experience at major research institutions including Lawrence Livermore National Laboratory and Barcelona Supercomputing Center, as well as industry experience as a Unix Systems Administrator at Digicel Jamaica. His work with the CODES network simulation toolkit demonstrates his technical expertise in network architecture evaluation and optimization.