Hyojin Kim
About Hyojin Kim
Hyojin Kim is a computer scientist with extensive experience in machine learning and computed tomography techniques. Currently employed at Lawrence Livermore National Laboratory, Kim has contributed to various research projects, including antiviral drug screening against COVID-19.
Work at Lawrence Livermore National Laboratory
Hyojin Kim has been employed at Lawrence Livermore National Laboratory (LLNL) since 2015 as a Computer Scientist. His work at LLNL includes contributions to antiviral drug screening efforts against COVID-19, utilizing AI-driven bioinformatics. He has also engaged in multi-modal image registration and fusion research. Prior to his current role, he served as Postdoctoral Research Staff at LLNL from 2013 to 2015 and participated in several summer scholar programs at the laboratory in 2009, 2011, and 2012.
Education and Expertise
Hyojin Kim holds a Doctor of Philosophy (Ph.D.) in Computer Science from the University of California, Davis. He also earned a Master of Science (M.S.) in Computer Science from the University of New Hampshire and a Bachelor of Science (B.S.) in Systems Management Engineering from Sungkyunkwan University. His expertise includes machine learning models for threat recognition, ill-posed reconstruction techniques for computed tomography applications, and high-performance computing.
Background
Hyojin Kim began his academic career at the University of New Hampshire, where he worked as a Graduate Research Assistant at the Space Science Center from 2005 to 2008. After completing his master's degree, he continued his research at UC Davis as a Graduate Student Researcher from 2008 to 2012. He also gained experience as a summer intern at Adobe's Advanced Technology Lab in 2010.
Achievements in Research and Development
Throughout his career, Hyojin Kim has developed machine learning models specifically for threat recognition in security applications. His research has significantly contributed to the field of bioinformatics, particularly in the context of antiviral drug screening during the COVID-19 pandemic. He has also focused on advanced techniques in image registration and fusion, applying high-performance and GPU computing to enhance research outcomes.