Sunghwan Kim
About Sunghwan Kim
Sunghwan Kim is a Staff Scientist at the National Institutes of Health with expertise in quantum chemical computations and a strong background in programming. He has contributed to significant projects like PubChem and has experience in mentoring and teaching in the field of chemistry.
Work at National Institutes of Health
Sunghwan Kim has been employed as a Staff Scientist at the National Institutes of Health (NIH) since 2007. His role involves conducting research that leverages his expertise in quantum chemical computations, specifically using ab initio and density functional theory (DFT) methods. He has contributed to various projects, including the PubChem project at the National Center for Biotechnology Information (NCBI), which serves as a significant chemical information resource.
Education and Expertise
Sunghwan Kim holds a Ph.D. in Physical Chemistry from The University of Georgia, completed between 2003 and 2007. He also earned a Master of Science in Inorganic Chemistry from Hanyang University, where he studied from 1999 to 2001. Additionally, he has pursued advanced studies in Public Health and Technology Transfer at the FAES Graduate School at NIH from 2014 to 2019. His educational background supports his expertise in quantum chemical computations and programming in languages such as C/C++, Python, R, Perl, and awk.
Current Editorial Roles
In addition to his scientific research, Sunghwan Kim serves as an Editorial Board Member for the journal of Biological Databases and Curation at Oxford University Press since 2016. He is also an Academic Editor for PLOS ONE, a role he has held since 2018. These positions reflect his commitment to advancing scientific communication and contributing to the academic community.
Mentoring and Teaching Experience
Sunghwan Kim has a strong background in mentoring and teaching at both undergraduate and graduate levels. His experience in education complements his research activities and enhances his ability to guide students and early-career researchers in their scientific endeavors.
Research Contributions and Skills
Sunghwan Kim has developed predictive models using machine learning techniques for chemical data analysis. His diverse skill set includes training in Technology Transfer and Public Health, which broadens his contributions beyond traditional chemistry roles. This combination of skills and experience positions him as a valuable asset in interdisciplinary research environments.