Kwangmoon Park

Background

I am a Statistics Ph.D. Candidate at University of Wisconsin-Madison, advised by Professor Sündüz Keleş. Before joining UW-Madison, I earned a master's degree in Statistics at the Yonsei University in 2020 and Professor Seung-Ho Kang was my academic advisor. I earned my B.A. in Economics and Statistics at Yonsei University, and I studied Economics as a visiting student at Erasmus Universiteit Rotterdam.

The problems that I aim to address are related to understanding how genes are regulated by distal regions in the genome, particularly by functional non-coding regions. To tackle these challenges, I develop statistical tools for analyzing High-dimensional genomic data, including Hi-C and HiChIP, and for linking diverse types of genomic or epigenomic data with better statistical interpretation. The specific methodologies I work on are closely related to tensor factorization/regression and dimension reduction techniques, including Partial Least Squares.

CV

Here is my CV.

Education

• Ph.D. in Statistics, University of Wisconsin-Madison (2020-Present)

• M.A. in Statistics, Yonsei University (2018-2020)

• Visiting student, Erasmus University Rotterdam (2017)

• B.A. in Economics and Statistics, Yonsei University (2012-2018)

Awards and Honors

• ENAR Distinguished Student Paper Award (2023)

- Eastern North American Region International Biometric Society

• ASA Section on Statistics in Genomics and Genetics (SGG) Student Paper Award (2023) 

- American Statistical Association (Section on Statistics in Genomics and Genetics)

• IMS Hannan Graduate Student Travel Award (2024) 

- Institute of Mathematical Statistics

Research

• Park, K., Keleş, S. (2023) Joint tensor analysis of single cell 3D genome and epigenetic data with Muscle, bioRxiv, Journal of the American Statistical Association, minor revision requested.

- This work won ENAR Distinguished Student Paper Award (2023). 

- This work won ASA Distinguished Student Paper Award (2023). 

• Park, K., Keleş, S. (2023) Sparse higher order partial least squares for simultaneous variable selection, dimension reduction, and tensor denoising, arxiv, under review.

- This work won IMS Hannan Graduate Student Travel Award (2024). 

• Park, K., Keleş, S. (2024) Empirical Bayes spline model learns multi-way genomic interactions from single cell 3D genome data, bioRxiv.

• Alberca, C., Park, K., Papale, L., Madrid, A., Keleş, S., Arlisch, R. (2024) Integration of multi-omics data improves the resolution of the molecular etiology of autism in a mouse model, in progress.

Presentations

• Joint Statistical Meetings (JSM), Washington, D.C.. Talk, August 10, 2022.

Denoising and inference for scHi-C by large-scale unbiased tensor decomposition

• Eastern North American Region (ENAR) International Biometric Society, Nashville TN. Talk, March 21, 2023.

Joint tensor modeling of single cell 3D genome and epigenetic data withMuscle.

• Midwest Machine Learning Symposium (MMLS), Chicago IL. Poster, May 17, 2023. 

Sparse higher order partial least squares for simultaneous variable selection, dimension reduction, and tensor denoising.

• Banff International Research Station (BIRS), Banff AB. Talk, July 3, 2023. 

Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle.

• Joint Statistical Meetings (JSM), Toronto ON. Talk, August 8, 2023.

Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle.

• University of Sydney Statistical Bioinformatics Seminar, virtual. Talk, April 15, 2023.

High dimensional tensor methods for multi-modal single cell genomics data.

Academic Service

• Reviewer for Recomb 2023.

• Reviewer for ISMB/ECCB 2023.

• Reviewer for Recomb 2024.