Seyoung Kim

Associate Professor
Department of Epidemiology
School of Public Health
University of Pittsburgh
Email : 's'ykim (replace the 's' with 'sss') at pitt.edu (or at acm.org)

Research interests: My main research interests lie in developing statistical machine learning techniques to address significant methodological problems in computational genomics. Recent advances in genome-wide profiling technology have allowed researchers to probe various aspects of biological systems on a system-wide scale, such as the transcriptome, proteome, metabolome, and epigenome. In addition, it is expected that in the future, genome sequencing will become a routine process that can be applied to a large number of individuals. Given the high-dimensional nature of genome-scale data in which many entities interact with each other in a complex manner, I'm interested in developing statistical machine learning techniques for understanding the genetic basis of diseases and disease-related biological processes with the ultimate goal of personalized medicine.

Bio: I received my B.S. in computer engineering from Seoul National University, Korea, and Ph.D. in from the University of California, Irvine. I was a postdoctoral fellow in Machine Learning Department at Carnegie Mellon University. I was an Assistant and Associate Professor in Computational Biology Department, School of Computer Science, Carnegie Mellon University until 2023. I was on parental leave during 2015 spring and 2016-2018 academic years for my two children. I received an NSF Career Award and Sloan Research Fellowship.

Publications

Doctoral students:
Richard Xu

Doctoral students (past):
Jun Ho Yoon (Ph.D., CBD, CMU, 2024)
Calvin McCarter (Ph.D., MLD, CMU, 2019)
Jing Xiang (Ph.D., MLD, CMU, 2017)