Computation, Data, and Society Lab
Our group is interested in
Developing computational and statistical methods,
Understanding and modelling data with AI-driven approches,
Solving real-world problems in the society
We specifically focus on developing and applying methods to mine complex data from various domains
Our current projects include:
Creating and developing statistical software programs based on techniques in machine learning
Studying artificial intelligence algorithms to better understand big data
Applying AI-driven approaches and statistical methods on datasets from fields such as biomedical sciences and social science
Publications:
* indicates Dr. Lee’s undergraduate students and ** indicates Dr. Lee's graduate students
Jai Woo Lee, Artificial Intelligence Methodologies with Probaiblistics Graphical Models and Large-Scale Computing, Under Review
**Donggeun Kim, **Sangjin Kim, **Xin Zan, **Kin Lok Wong, and Jai Woo Lee, The Role of Artificial Intelligence and Big Data Methodologies in Social Media Misinformation, Under Review
**Sangjin Kim and Jai Woo Lee, AI-Powered Approaches in ADMET Prediction with Computational Modeling, Under Review
**Juyong Ko and Jai Woo Lee, Stress Detection Approach Using Artificial Intelligence Techniques, Under Review
Jai Yeon Lee and Jai Woo Lee, A Survey of Current Trends in AI-Driven Scaffolding in Education, Under Review
Jai Woo Lee, Integrating AI technology and omics tools in cancer management, Accepted
**Juyong Ko, **Donggeun Kim, **Sangjin Kim, Jai Woo Lee, Datafication with Hybrid Intelligence for Planetary Solutions with a Global Big Data Environment, Under Review
**Sangjin Kim, **Donggeun Kim, **Juyong Ko, **Xin Zan, **Kin Lok Wong, **Yujing Mao, **Lakhwinder Kaur, **Hyeonjun Nam, and Jai Woo Lee, Transforming Cutting-Edge Healthcare: Emerging Trends in Metabolomics and Drug Design Using Artificial Intelligence and Big Data Methodologies, Under Review
**Sangjin Kim, *Dongha Kim, *Donghyeok Choi, *Seung Woo Kim, *Minho Sun, Jai Woo Lee, AI-Driven Techniques with Probabilistic Graphical Models and Image Processing Tools in ADMET analysis, Accepted
**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.
**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
**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
**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)
**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)
**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
**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
Lee, J. W. (2024). Commissioned Book Review: Elena Llaudet and Kosuke Imai (2022). Data Analysis for Social Science: A Friendly and Practical Introduction. Political Studies Review, https://doi.org/10.1177/14789299241270622
Seo, S., Lee, J.W. (2024). Applications of Big Data and AI-Driven Technologies in CADD (Computer-Aided Drug Design). In: Gore, M., Jagtap, U.B. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 2714. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3441-7_16
*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
Haerang Park, Jai Woo Lee; The Network Structure of Sovereign and Corporate Credit Risk, The Korea Journal of BigData. 2022, vol.7, no.2, pp. 225-234. DOI: 10.36498/kbigdt.2022.7.2.225
Jai Woo Lee, Miguel A. Maria-Solano, Thi Ngoc Lan Vu, Sanghee Yoon, Sun Choi; Big data and artificial intelligence (AI) methodologies for computer-aided drug design (CADD). Biochem Soc Trans 28 February 2022; 50 (1): 241–252. DOI: https://doi.org/10.1042/BST20211240
Suh D, Lee JW, Choi S, Lee Y. Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction. International Journal of Molecular Sciences. 2021; 22(11):6032. DOI: https://doi.org/10.3390/ijms22116032
Lazim R, Suh D, Lee JW, Vu TNL, Yoon S, Choi S. Structural Characterization of Receptor–Receptor Interactions in the Allosteric Modulation of G Protein-Coupled Receptor (GPCR) Dimers. International Journal of Molecular Sciences. 2021; 22(6):3241. DOI: https://doi.org/10.3390/ijms22063241
Jai Woo Lee, Jie Zhou, Erika L. Moen, Tracy Punshon, Anne G. Hoen, Megan E. Romano, Margaret R. Karagas, Jiang Gui, Prediction of an outcome using NETwork Clusters (NET-C), Computational Biology and Chemistry, Volume 90, 2021, 107425, ISSN 1476-9271, DOI: https://doi.org/10.1016/j.compbiolchem.2020.107425
Jai Woo Lee, Erika L. Moen, Tracy Punshon, Anne G. Hoen, Delisha Stewart, Hongzhe Li, Margaret R. Karagas, Jiang Gui, An Integrated Gaussian Graphical Model to evaluate the impact of exposures on metabolic networks, Computers in Biology and Medicine, Volume 114, 2019, 103417, ISSN 0010-4825, DOI: https://doi.org/10.1016/j.compbiomed.2019.103417
Jai Woo Lee, Tracy Punshon, Erika L. Moen, Margaret R. Karagas, Jiang Gui, Penalized estimation of sparse concentration matrices based on prior knowledge with applications to placenta elemental data, Computational Biology and Chemistry, Volume 71, 2017, Pages 219-223, ISSN 1476-9271, DOI: https://doi.org/10.1016/j.compbiolchem.2017.10.012
Working Papers
Hyeonjun Nam and Jai Woo Lee, TBA, In Preparation
Lahkwinder Kaur and Jai Woo Lee, TBA, In Preparation
Yujing Mao and Jai Woo Lee, TBA, In Preparation
Kin Lok Wong and Jai Woo Lee, TBA, In Preparation
Xin Zan and Jai Woo Lee, TBA, In Preparation
Juyong Ko and Jai Woo Lee, AI-Based Assessment of the Associations Between Lifestyle Factors and Mental Health Outcomes (In Preparation)
Sangjin Kim and Jai Woo Lee, AI-Assisted Drug Discovery Platform (In Preparation)
Donggeun Kim and Jai Woo Lee, Development of a Financial Risk Model Using Artificial Intelligence Techniques with Demographic Factors (In Preparation)