Broadly speaking, my research interest lies in studying complex data structures in Statistics and investigating statistical relationships between such complicated data. I am particularly interested in multivariate, functional, and object data, bootstrap inference, robust statistics, dependent data, and causal inference. See my PhD thesis , Google Scholar profile, and Github repositories.
* Corrections for published papers are summarized here.
Publications
Yeon, H. (2026+) Gaussian and bootstrap approximation for functional principal component regression. Under revision [ArXiv]
Lopez-Pintado, S., Dai, X., Yeon, H., Yao, Z., and Alvarez-Liebana, J. (2026+) Multivariate functional depth-based envelope test, Under revision
Bočinec, F.,* Nagy, S., and Yeon, H. (2026+) Projection detph for functional data: Theoretical properties. Under revision [Arxiv]
Yeon, H., Dai, X. and Nordman, D.J. (2026+) Wild bootstrap for mean response inference in functional linear regression models. Under revision [Arxiv]
Yeon, H. (2026+) Inference for function-on-function regression: central limit theorem and residual bootstrap. Accepted [Arxiv]
Yeon, H., Dai, X. and Lopez-Pintado, S. (2025) Regularized halfspace depth for functional data. Journal of Royal Statistical Society, Series B, 87(5), 1553–1575 [Link]
In the process of publication, the package was not provided with the paper. Instead, the most updated version can be found in my GitHub repository.
Yeon, H., Dai, X. and Nordman, D.J. (2024) Bootstrap inference in functional linear regression models with scalar response under heteroscedasticity. Electronic Journal of Statistics, 18(2), 3590–3627 [Link]
Yeon, H., Dai, X. and Nordman, D.J. (2023) Bootstrap inference in functional linear regression models with scalar response. Bernoulli, 29(4), 2599–2626 [Link]
Submitted manuscripts
Yeon, H., Dai, X. and Lopez-Pintado, S. (2026+) Conditional regularized halfspace depth for sparse functional data and its applications [ArXiv]
Yeon, H. and Kokoszka, P. (2026+) Bootstrap two-sample tests for functional regression
Bočinec, F.,* Nagy, S., and Yeon, H. (2026+) Projection depth for functional data: Practical issues, computation and applications [ArXiv]
Yeon, H. (2026+) Effective and flexible depth-based inference for functional parameters [ArXiv]
Son, D.,* Yang, S., Reich, B., and Yeon, H. (2026+) Causal inference with point processes
Manuscripts in preparation
Gnettner, F.,* Yeon, H., and Kokoszka, P. (2026+) Dimension-invariant uniform consistency of the empirical spatial distribution function and its associated spatial depth estimator. [ArXiv]
Yeon, H. and Kokoszka, P. (2026+) Change points detection for functional data
Böhm, I.,* Bočinec, F.,* Nagy, S., and Yeon, H. (2026+) Data depth for spherical data
Yeon, H. and Westling, T. (2026+) Causal inference for functional data
Chang, W. and Yeon, H. (2026+) Statistical inference for complex functional data analysis
Abdurakhmanov, B.,* Yeon, H., and Kokoszka, P. (2026+) Statistical inference for functional generalized linear models
Yeon, H. and Kuchibhotla, A. K. (2026+) Honest inference for functional parameters
Yeon, H. and Lopez-Pintado, S. (2026+) Causal inference for complex data
Yeon, H. (2026+) Data depth for density data
Technical reports
Yeon, H. (2025) Generalization of theoretical results in "Bootstrap inference in functional linear regression models with scalar response". Unpublished technical report [Link]
Yeon, H., Dai, X. and Nordman, D.J. (2024) Supplement to "Bootstrap inference in functional linear regression models with scalar response under heteroscedasticity". Iowa State University Digital Repository [Link]
Software development
BTSinFLRM - Developer [Github]
An R package for bootstrap inference in functional linear regression models:
- confidence intervals for mean responses or projections using residual, paired, and wild bootstrap methods.
RHD - Developer [Github]
An R package for computing the regularized halfspace depth for dense and sparse functional data.
DepthInfer - Developer [Github]
An R package that conducts statistical inference for infinite-dimensional parameters using functional depth statistics
Talks
2026 CMStatistics, Berlin, Germany (Invited, Online) Dec 2026
EcoSta, Tokyo, Japan (Invited, Online) Aug 2026
NESS, Storrs, CT, USA (Invited) May 2026
GMU, Department of Statistics, Fairfax, VA, USA (Seminar) May 2026
UNCC, Department of Mathematics and Statistics, Charlotte, NC, USA (Seminar) Mar 2026
SDSU, Department of Mathematics and Statistics, Brookings, SD, USA (Seminar, Online) Mar 2026
UPitt, DEpartment of Statistics, Pittsburgh, PA, USA (Seminar) Mar 2026
UMass Lowell, Department of Mathematics and Statistics, Lowell, MA, USA (Seminar) Feb 2026
UofSC, Department of Statistics, Columbia, SC, USA (Colloquium) Feb 2026
WFU, Department of Statistics, Winston-Salem, NC, USA (Colloquium) Feb 2026
2025 CMStatistics, London, UK (Invited, Online) Dec 2025
EcoSta, Tokyo, Japan (Contributed, Online) Aug 2025
2024 CMStatistics, London, UK (Invited, Online) Dec 2024
ICORS, Fairfax, VA, USA (Invited) Jul 2024
KSU, Department of Mathematical Sciences, Kent, OH, USA (Seminar) Mar 2024
NCSU, Department of Statistics, Raleigh, NC (Seminar, Online) Feb 2024
2023 CMStatistics, Berlin, Germany (Invited, Online) Dec 2023
EcoSta, Tokyo, Japan (Contributed, Online) Aug 2023
UW, Department of Statistics, Seattle, WA, USA (Seminar, Online) Feb 2023
2022 CMStatistics, London, UK (Invited, Online) Dec 2022
UIUC, Department of Statistics, Champaign, IL, USA (Seminar) Dec 2022
JSM, Washington DC, USA (Topic-contributed) Aug 2022
ICORS, Waterloo, Ontario, Canada (Contributed, Online) Jul 2022
ISNPS, Paphos, Cyprus (Contributed) Jun 2022
Services
Referee services (25):
Advances in Data Analysis and Classification (2)
Annals of Applied Statistics (1)
Annals of Statistics (1)
Communications in Statistics - Simulation and Computation (2)
Computational Statistics and Data Analysis (1)
Electronic Journal of Statistics (1)
Frontiers in Psychology (Personality and Social Psychology) (1)
Humanities and Social Sciences Communications (1)
International Journal of Approximate Reasoning (1)
International Statistical Review (1)
Journal of Computational and Graphical Statistics (2)
Journal of Econometrics (1)
Journal of Multivariate Analysis (1)
Journal of Nonparametric Statistics (1)
Journal of Royal Statistical Society, Series B (Statistical Methodology) (2)
Journal of the American Statistical Association (1)
Journal of Time Series Analysis (2)
Sankhya A (1)
Scandinavian Journal of Statistics (1)
Statistics and Computing (1)
Statistics in Medicine (1)
Invited session organizer
2026 CMStatistics, Berlin, Germany Dec 2026
Functional data meet machine learning
EcoSta, Tokyo, Japan (Session EO184) Aug 2026
Inference using resampling methods in modern statistics and machine learning
JSM, Boston, MA, USA Aug 2026
Recent developments of resampling methods for complex data
NESS, Storrs, CT, USA May 2026
Real‑world applications of statistical analysis for complex data
Recent developments of statistical methodologies for functional data
2025 CMStatistics, London, UK (Session CO197) Dec 2025
Data depth in statistics and machine learning
2024 ICORS, Fairfax, VA, USA (S22) July 2024
Recent Development Of Data Depth And Its Statistical Applications
Committee
2026 CMStatistics, Berlin, Germany Dec 2026
Scientific Program Committee
NESS, Storrs, CT, USA May 2026