Jae Seung Yeom
About Jae Seung Yeom
Jae Seung Yeom is a computer scientist currently working at Lawrence Livermore National Laboratory, where he focuses on simulating epidemics and optimizing solver libraries. He has a diverse academic background, holding degrees in Astronomy and Computer Science from Yonsei University and Virginia Tech, respectively.
Work at Lawrence Livermore National Laboratory
Jae Seung Yeom has been employed at Lawrence Livermore National Laboratory since 2017 as a Computer Scientist. His work involves simulating epidemics over co-evolving networks of dynamically interacting human populations. He also engages in data-driven modeling and optimizing the performance of solver libraries for sparse linear systems. Prior to his current role, he served as a Postdoctoral Researcher at the same institution from 2014 to 2016, contributing to various research initiatives.
Education and Expertise
Jae Seung Yeom holds multiple degrees in relevant fields. He earned a Bachelor of Science in Astronomy from Yonsei University, which he completed from 1992 to 1999. He also obtained a Bachelor of Science in Computer Science from Yonsei University from 1994 to 2000. Yeom furthered his education at Virginia Tech, where he achieved a Ph.D. in Computer Science from 2007 to 2011. Additionally, he received a Master of Science in Information Networking from Carnegie Mellon University, studying from 2001 to 2003.
Research Experience
Yeom has extensive research experience, having worked as a Research Assistant at Carnegie Mellon University in various capacities from 2003 to 2006 and at Virginia Tech from 2008 to 2014. His research projects have focused on modeling the multi-scale evolutionary dynamics of RNA virus populations and the performance of optimistic/reversible parallel discrete event simulations. He has also been involved in detecting objects of interest in radiographic images.
Background
Jae Seung Yeom's academic journey began at Yonsei University, where he pursued studies in Astronomy and Computer Science. His transition to advanced research roles occurred at Carnegie Mellon University and Virginia Tech, where he gained valuable experience in computational methods and simulations. His current role at Lawrence Livermore National Laboratory builds on this foundation, focusing on complex systems and data-driven approaches.