Dr. Kim is an Assistant Professor at the Center for Secure Artificial Intelligence for Healthcare in the School of Biomedical Informatics at the University of Texas Health Science Center at Houston. She received her PhD in computer science with specific expertise in machine learning for health data. She has served as program committee of various prestigious data science and/or medical informatics conferences such as WWW, AAAI, IJCAI, AMIA, KDD Workshops on Applied Data Science for Healthcare, ACM-BCB, IEEE-ICHI, IEEE-BIBM, and also served as reviewer for JAMA Open Network, Journal of American Medical Informatics, Journal of Biomedical Informatics, and Nature Scientific Reports. She is the co-organizer of SBMI Machine Learning Hackathon series and the program committee of Cerner/SBMI National Data Science Challenge.

Dr. Kim’s current research interest is to harmonize multimodal data to identify counterfactual outcomes of controllable risk factors and/or treatments. Her main focus is causal analysis (heterogeneous treatment effect analysis, counterfactual analysis, Bayesian Network modeling), network modeling (multimodal data harmonization, knowledge representation), and computational phenotyping (temporal clustering, multimodal data clustering), with special emphasis on analyzing neurodegenerative diseases including Alzheimer’s disease.

Education & Training

PhD, Computer Science, 2017, Pohang University of Science and Technology
BS, Industrial Engineering, 2012, Pohang University of Science and Technology

Research

• Data Mining
• Machine Learning
• Computational Phenotyping