Sungbum Hong is an associate professor and machine learning researcher with over two decades of experience spanning distributed systems, algorithms, and applied ML for national-security and scientific problems. Currently at Lawrence Livermore National Laboratory, he develops models to infer cyclomatic complexity from control-flow graph data, combining deep algorithmic insight with practical Python and LaTeX workflows. He previously served as faculty at Jackson State University teaching operating systems, data structures and parallel systems while publishing on distributed algorithms and systems. His research pedigree includes a PhD and postdoc in distributed systems and an ONR Summer Faculty fellowship exploring GANs on numerical datasets, reflecting a rare blend of theoretical rigor and experimental ML. Early industry experience building communication software and databases informs his pragmatic approach to research translation and systems design. Colleagues describe him as an eager collaborator who continually adopts new tools to tackle interdisciplinary challenges.
16 years of coding experience
3 years of employment as a software developer
Master of Science (MS), Computer Science, Master of Science (MS), Computer Science at The University of Tennessee at Chattanooga
Bachelor of Engineering (BE), Electrical and Electronics Engineering, Bachelor of Engineering (BE), Electrical and Electronics Engineering at Kookmin University
Ph.D, Interdisciplinary program in Information Science, Ph.D, Interdisciplinary program in Information Science at University of North Texas
Post doc; Research Associate, Distributed Systems and Algorithms, Post doc; Research Associate, Distributed Systems and Algorithms at University of North Texas, Computer Scienc
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