People

• BS in Computer Science and BS in Mathematics from Carnegie Mellon University 

• MS in Computer Science at Dartmouth College 

• PhD in Quantitative Biomedical Sciences from Geisel School of Medicine at Dartmouth College 

• Division Chair, Division of Exploratory Studies, College of Public Policy

• Associate Professor, Department of Big Data Science 

(Graduate School)  

• Affiliated Associate Professor, Interdisciplinary Major Program in Bio Medical and Data Science Convergence (Graduate School) 

• Affiliated Associate Professor, Division of Big Data Science

• Adjunct Associate Professor, Convergence Major in Smart Eco City, College of Science and Technology  

• Adjunct Associate Professor, Department of Advanced Convergence Pharmaceutical Sciences, College of Pharmacy  

• Adjunct Professor, Institute of Statistics and Applied Mathematics, Anhui University of Finance and Economics, China

• Committee Member, Sejong City Data Committee 

1. Sangjin Kim, Jai Woo Lee, Chapter 13 - AI technologies for precision and personalized medicine, Editor(s): Jen-Tsung Chen, Revolutionizing Drug Development, Academic Press, 2026, Pages 199-209, ISBN 9780443340598, https://doi.org/10.1016/B978-0-443-34059-8.00009-9.  

2. Kim, S., Lee, S., Jin, S., & Lee, J. W. (2025). AI Tools and Applications in Managing Immunological Disorders. In J. Chen (Ed.), AI-Assisted Computational Approaches for Immunological Disorders (pp. 39-62). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9725-1.ch002  

3. Sangjin Kim & Jai Woo Lee (2025) Text as Data: A New Framework for Machine Learning and the Social Sciences, Technometrics, 67:2, 358-359, DOI: 10.1080/00401706.2025.2485656  (Q1 in Statistics & Probability in SCIE edition)  

4. SANGJIN KIM and JAI WOO LEE. (2024). Predicting Hypoxia and Estimating the Interactions of Ewe Metabolites Using Machine Learning Techniques. Journal of the Korean Society for Industrial and Applied Mathematics, 28(4), 226-242. https://doi.org/10.12941/jksiam.2024.28.226  

5. Donggeun Kim, Sangjin Kim, Juyong Ko, Jai Woo Lee; “A Big Data-Driven Business Data Analysis System: Applications of Artificial Intelligence Techniques in Problem Solving” The Korea Journal of BigData, 2023, vol.8, no.1, pp. 35-47. DOI: 10.36498/kbigdt.2023.8.1.35  

1. Juyong Ko, Juwon Kim, Dongha Kim, Hyeonjun Nam, and Jai Woo Lee. 2025. Applications of Data-Driven Approaches Using Artificial Intelligence Algorithms and Quantum Computing in Sustainability. In Proceedings of the Sixth International Conference on Digital Age & Technological Advances for Sustainable Development (DATA '25). Association for Computing Machinery, New York, NY, USA, 81–86. https://doi.org/10.1145/3747897.3747911 

2. JUYONG KO and JAI WOO LEE. (2024). Applications of Big Data and AI-Driven Technologies in High-Dimensional Data Analysis: Taiwanese Bankruptcy Prediction Using Machine Learning Models with Factor Analysis. Journal of the Korean Society for Industrial and Applied Mathematics, 28(4), 286-302. https://doi.org/10.12941/jksiam.2024.28.286  

3. Donggeun Kim, Sangjin Kim, Juyong Ko, Jai Woo Lee; “A Big Data-Driven Business Data Analysis System: Applications of Artificial Intelligence Techniques in Problem Solving” The Korea Journal of BigData, 2023, vol.8, no.1, pp. 35-47. DOI: 10.36498/kbigdt.2023.8.1.35  

1. Kim, D., & Lee, J. W. (2025). Predicting Absenteeism at Workplace Using Machine Learning and Network Analysis. SAGE Open, 15(2). https://doi.org/10.1177/21582440251336019 (Original work published 2025)  (Q1 in SOCIAL SCIENCES, INTERDISCIPLINARY in SSCI edition) 

2. Donggeun Kim, Sangjin Kim, Juyong Ko, Jai Woo Lee; “A Big Data-Driven Business Data Analysis System: Applications of Artificial Intelligence Techniques in Problem Solving” The Korea Journal of BigData, 2023, vol.8, no.1, pp. 35-47. DOI: 10.36498/kbigdt.2023.8.1.35