Updated in May, 2026
About

Any statistical and computational methods operate under the constraints imposed by the data generating process. As such, I study how evolutionary processes shape statistical inference.
I’m currently working on the following topics:
- Evolutionary basis of statistical genetics
- Random dynamical systems on manifolds
Contact: hblee@umich.edu
Education
University of Michigan, Ann Arbor
- Doctor of Philosophy, Department of Statistics (2024.9 -)
Seoul National University
- Bachelor of Mathematics, Department of Mathematical Sciences (2017.3 - 2023.8)
- Doctor of Medicine, Department of Medicine (2016.3 - 2023.8)
Professional service
Peer review
International Journal of Epidemiology, Nature Communications, Genetics (GSA), HGG Advances, BMC Medical Research Methodology, NAR Genomics and Bioinformatics
Publications
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*: Equal contribution
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Preprints
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Hanbin Lee,
and Jonathan Terhorst
Parameterizing the genetic architecture under stabilizing selection.
biorxiv,
2026
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Hanbin Lee,
and Jonathan Terhorst
Parameterizing the genetic architecture under stabilizing selection.
biorxiv,
2026
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Journals
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Hanbin Lee,
Nathaniel S. Pope, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
Genetic prediction with ARG-powered linear algebra.
Genetics, in press,
2026
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Brieuc Lehmann,
Hanbin Lee, Luke Anderson-Trocme, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
On ARGs, pedigrees, and genetic relatedness matrices.
Genetics,
2026
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Hanbin Lee,
Rosalind F. Craddock, Gregor Gorjanc, and Hannes Becher
randPedPCA: Rapid approximation of principal components from large pedigrees.
Genetics Selection Evolution,
2025
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Hanbin Lee*, Moo Hyuk Lee*,
Kangcheng Hou, Bogdan Pasaniuc, and Buhm Han
Admixed and single-continental genome segments of the same ancestry have distinct linkage disequilibrium patterns.
Genome Biology,
2025
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Hanbin Lee,
and Buhm Han
Pseudobulk with proper offsets has the same statistical properties as generalized linear mixed models in single-cell case-control studies.
Bioinformatics,
2024
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Hanbin Lee,
and Buhm Han
FastRNA: an efficient exact solution for PCA of single-cell RNA sequencing data based on a batch-accounting count model.
American Journal of Human Genetics,
2022
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Hanbin Lee,
and Buhm Han
A theory-based practical solution to correct for sex-differential participation bias.
Genome Biology,
2022
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Chanwoo Kim*, Hanbin Lee*,
Juhee Jeong, Keehoon Jung and Buhm Han
MarcoPolo: a clustering-free approach to the exploration of differentially expressed genes along with group information in single-cell RNA-seq data.
Nucleic Acids Research,
2022
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Hanbin Lee,
Nathaniel S. Pope, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
Genetic prediction with ARG-powered linear algebra.
Genetics, in press,
2026