K² Lab · Kangjin Kim Lab

Biostatistics, Bioinformatics, and Biomedical AI

Department of Applied Statistics, Gachon University

We use statistics, bioinformatics, and data science to analyze complex biomedical data, from omics and respiratory disease to environmental health and precision medicine.

Meet the Lab → Prospective students →

Research

Research Areas

People

Lab Members

Principal Investigator

Kangjin Kim portrait

Kangjin Kim, PhD

김강진

Principal Investigator

Assistant Professor · Department of Applied Statistics, Gachon University
Email: kim0616@gachon.ac.kr
Research interests: Statistical methodology, Biostatistics, Survival analysis, Prediction modeling, Statistical genetics, Rare variant analysis, Multi-omics, Bioinformatics, Biomedical AI, Respiratory disease data science

Kangjin Kim’s research focuses on statistical and computational methods for high-dimensional biomedical data, with applications to statistical genetics, multi-omics, survival and prediction modeling, respiratory disease, and precision medicine.

Education
BS in Statistics; MPH/PhD in Biostatistics
Postdoctoral Research
Harvard Medical School and Brigham and Women’s Hospital

Graduate Students

Jihyeon Lee portrait

Jihyeon Lee

이지현

Master’s Student

Department of Applied Statistics, Gachon University
Email: dlwlgus1998@gachon.ac.kr
Research interests: Biostatistics, data analysis, aging, cognitive decline, inflammation, healthcare decision-making

Her research focuses on aging, cognitive decline, and inflammation based on biostatistics and data analysis, with the goal of contributing to data-driven decision-making in healthcare.

Jun-Jae Won portrait

Jun-Jae Won

원준재

Master’s Student

Department of Applied Statistics, Gachon University
Email: wonjunjae49@gmail.com
Links: Google Scholar
Research interests: Biostatistics, survival analysis, causal inference, microbiome data analysis, high-dimensional biological data

His research interests include biostatistics, survival analysis, causal inference, and microbiome data analysis, with a focus on developing statistical methods for high-dimensional biological data. He is involved in sTMAT, PRISM-AE, and NAFLD-CKD propensity score analysis projects.

Eunjae Han portrait

Eunjae Han

한은재

Master’s Student

Department of Applied Statistics, Gachon University
Email: ejhan02@gachon.ac.kr
Links: GitHub
Research interests: Biostatistics, data analysis, healthcare decision-making, artificial intelligence, digital wellness, health risk prediction

Her research interests include clinical statistics, digital wellness, and individual health risk prediction using large public health data. She is interested in modeling non-linear relationships between lifestyle factors such as sleep and nutrition and metabolic syndrome.

Undergraduate Researchers

Seoyoung Bae portrait

Seoyoung Bae

배서영

Undergraduate Student

Department of Applied Statistics, Gachon University
Email: s44v44t44@gachon.ac.kr
Research interests: Statistical learning, microbiome data analysis, integrative biomedical data analysis, environmental health data analysis

Her research interests include statistical learning, microbiome data analysis, and integrative analysis of biomedical and environmental health data.

Na Yoon Kim portrait

Na Yoon Kim

김나윤

Undergraduate Student

Department of Applied Statistics, Gachon University
Email: green09170@gachon.ac.kr
Research interests: Medical big data, statistical analysis, clinical data analysis, biomarkers, COPD, healthcare outcomes

Her interests include medical big data and statistical analysis, with a goal of using data analytics to uncover meaningful patterns that can improve healthcare outcomes. She is currently involved in a project on statistical analysis of clinical data and biomarkers for COPD.

Funded Projects

Grants and Funded Projects

Current externally funded and commissioned research projects.

Lab Life

Lab Life

Publications

Selected Publications

Respiratory Disease and COPD

  1. Kim, W.*, Hu, X.*, Kim, K.*, Chun, S., Orchard, P., Qiao, D., ... & Cho, M. H. (2026). Whole genome sequence analysis of pulmonary function and COPD in 44,287 multi-ancestry participants. Genome Biology.
  2. Wan, E., Yen, A., Elalami, R., Grumley, S., Kim, K., Estépar, R., ..., Silverman, E., Cho, M., Diaz, A.† (2025). Airway mucus plugs on chest computed tomography are associated with future exacerbations in chronic obstructive pulmonary disease. Journal of Respiratory and Critical Care Medicine.
  3. Kim, K., Park, S., Choi, S., Won, S.† (2025). Robust Phylogenetic Tree-based Microbiome Association Test using Repeatedly Measured Data for Composition Bias. BMC Bioinformatics.
  4. Yie, G. E., Kim, N. E., Park, S. C., Kim, K., Shin, S., Lee, S. K., ... & Won, S. (2025). Comparison of extracellular vesicles carrying bacterial DNA in urine and serum from a Korean population. Frontiers in Microbiology, 16, 1616528.
  5. Diaz, A., Grumley, S., Yen, A., Sonavane, S., Elalami, R., Abdalla, M., Kim, K., Nardelli, P., ..., Cho, M.† (2024). Eosinophils, mucus plugs, and clinical outcomes: Findings from two COPD cohorts. European Respiratory Journal.
  6. Kim, Y.*, Choi, S.*, Sohn, K., Jung, J., Kim, H., Park, J., Kim, K., Kang, M., Yang, M., Kim, S., Kim, S., Lee, J., Choi, J., Park, H., Lee, S., Kim, S., Park, J., Cho, S., Won, S., Yi, H., Kang, H.† (2022). Selenomonas: A marker of asthma severity with the potential therapeutic effect. Allergy, 77(1), 317-320.
  7. Hong, S.*, Kim, K.*, Baek, M., Yi, H., Lee, S., Kim, D., Lee, C., Shin, C., Rhee, C.† (2022). Association of obstructive sleep apnea severity with the composition of the upper airway microbiome. Journal of Clinical Sleep Medicine, 18(2), 505-515.

Methods and Software

  1. Kim, K., Won, S.† (2026). All-inclusive Microbiome Association Analysis (AMAA) package based on multiple 16S rRNA databases. Computers in Biology and Medicine. Under review.
  2. Kim, K., Park, S., Choi, S., Won, S.† (2025). Robust Phylogenetic Tree-based Microbiome Association Test using Repeatedly Measured Data for Composition Bias. BMC Bioinformatics.
  3. Kim, K., Park, J., Park, S., & Won, S.† (2020). Phylogenetic tree-based microbiome association test. Bioinformatics, 36(4), 1000-1006.

Multi-omics, Microbiome, and Biomedical Applications

  1. Yie, G. E., Kim, N. E., Park, S. C., Kim, K., Shin, S., Lee, S. K., ... & Won, S. (2025). Comparison of extracellular vesicles carrying bacterial DNA in urine and serum from a Korean population. Frontiers in Microbiology, 16, 1616528.
  2. Heo, M., Park, Y. S., Yoon, H., Kim, N. E., Kim, K., Shin, C. M., ... & Lee, D. H.† (2023). Potential of Gut Microbe-Derived Extracellular Vesicles to Differentiate Inflammatory Bowel Disease Patients from Healthy Controls. Gut and Liver, 17(1), 108-118.
  3. Lee, Y., Park, J., Lee, J., Gim, J., Do, A., Jo, J., Park, J., Kim, K., Park, K., Jin, H., Choi, K., Kang, S., Kim, H., Kim, S., Moon, S., Farrer, L., Lee, G.†, Won, S.† (2023). Heritability of cognitive abilities and regional brain structures in middle-aged to elderly East Asians. Cerebral Cortex, 1-12.
  4. Kim, K., Lee, S., Park, S., Kim, N., Shin, C., Lee, S., Jung, Y., Yoon, D., Kim, H., Kim, S., Hwang, G., Won, S.† (2022). Role of an unclassified Lachnospiraceae in the pathogenesis of type 2 diabetes: a longitudinal study of the urine microbiome and metabolites. Experimental & Molecular Medicine, 54(8), 1125-1132.
  5. Kim, K., Lee, Y., & Won, S.† (2022). Relative contributions of the host genome, microbiome, and environment to the metabolic profile. Genes & Genomics, 1-9.
  6. Park, J., Lutz, S. M., Choi, S., Lee, S., Park, S. C., Kim, K., Choi, H., Park, H., Lee, S., Weiss, S., Hong, S., Kim, B.†, Won, S.† (2021). Multi-omics analyses implicate EARS2 in the pathogenesis of atopic dermatitis. Allergy, 76(8), 2602-2604.
  7. Nah, G., Park, S. C., Kim, K., Kim, S., Park, J., Lee, S.†, & Won, S.† (2019). Type-2 Diabetics Reduces Spatial Variation of Microbiome Based on Extracellular Vesicles from Gut Microbes across Human Body. Scientific Reports, 9(1), 1-10.
  8. Lee, M., Kang, M., Lee, S., Lee, E., Kim, K., Won, S., Suh, D., Kim, K. W., Sheen, Y., Ahn, K., Kim, B.† & Hong, S.† (2018). Perturbations of gut microbiome genes in infants with atopic dermatitis according to feeding type. Journal of Allergy and Clinical Immunology, 141(4), 1310-1319.
  9. Lee, E., Lee, S. Y., Kang, M. J., Kim, K., Won, S., Kim, B., Choi, K., Kim, B., Cho, H., Kim, Y., Yang, S., Hong, S.† (2016). Clostridia in the gut and onset of atopic dermatitis via eosinophilic inflammation. Annals of Allergy, Asthma & Immunology, 117(1), 91-92.

AI, Prediction Modeling, and Environmental Health

  1. Lee, G., Kim, K., & Jang, J. (2023). Real-time path planning of controllable UAV by subgoals using goal-conditioned reinforcement learning. Applied Soft Computing, 110660.
  2. Lee, G. T., & Kim, K.† (2023). A Controllable Agent by Subgoals in Path Planning using Goal-Conditioned Reinforcement Learning. IEEE Access, 11, 33812-33825.
  3. Lee, G. T., & Kim, K.† (2023). Abnormal Chamber Detection in the Etching Process Using Time-Series Data Augmentation and Soft Labeling. IEEE Sensors Journal, 23(5), 5084-5093.
  4. Guak, S., Kim, K., Yang, W., Seo, S., Won, S., Lee, K.† (2020). Prediction models using outdoor environmental data for real-time PM10 concentrations in daycare centers, kindergartens, and elementary schools. Building and Environment, 187, 107371.

Working Papers and Ongoing Projects

  1. Kim, K., Nath, H., Grumley, S., Orejas, J., Dolliver, W., Mettler, S., Yen, A., Jacobs, K., Manapragada, P., Abozeed, M., Aziz, M., Zahid, M., Sonavane, S., Trans-Omics in Precision Medicine (TOPMed), Silverman, E., Bowler, R., Diaz, A., Cho, M. Whole genome sequencing and proteomic analysis of mucus plugging in COPDGene and ECLIPSE.
  2. Kim, K., Hu, X., Chun, S., Gharib, S., ..., Trans-Omics in Precision Medicine (TOPMed), Manichaikul, A., Silverman, E., Cho, M. Whole genome sequencing analysis of severe, early-onset chronic obstructive pulmonary disease.

For Students

Prospective graduate and undergraduate students

Students interested in statistics, data science, bioinformatics, biomedical data analysis, or AI/ML for healthcare may contact the lab after reviewing the research areas and current projects. Prior experience is helpful, but students are not expected to know everything in advance.

Students gradually build research skills through ongoing projects, reproducible analysis, and scientific writing.

통계학, 데이터사이언스, 바이오인포매틱스, 의생명 데이터 분석, AI/ML 기반 헬스케어 연구에 관심 있는 학생은 연구실의 연구 분야를 살펴본 뒤 문의할 수 있습니다. 관련 경험이 있으면 도움이 되지만, 모든 것을 처음부터 갖추고 있을 필요는 없습니다.

Contact

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Affiliation
Department of Applied Statistics, Gachon University
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