Dr. Hyonho Chun

Adjunct Associate Professor, Department of Statistics, Purdue University, 2018-
Associate Professor, Department of Mathematics and Statistics, Boston University , 2018-

Associate Professor, Department of Statistics, Purdue University, 2016-2017
BrainPool Visiting Professor, Mathematical Sciences, KAIST, 2016
Assistant Professor, Statistics, Purdue University, 2010-2016
Postdoctoral Associate, Epidemiology and Public Health, Yale University, 2009- 2010
Ph. D. Statistics, University of Wisconsin at Madison, 2008
M. S. Statistics, Seoul National University, 2002
B. S. Earth Science Education, Seoul National University, 2000


We recently moved to Boston University.
Email: chunh@purdue.edu
or chunh@bu.edu

Research Interests:

Network inference and covariance estimation for high dimensional data.
Statistical genomics.
Computer model calibration and statistical quality control.
Statistical theory and methods for correlated high dimensional low sample size data.
Nonparametric function estimation and machine learning.

Research Assistants:


Qingyi Gao (Ph. D. Student at Department of Statistics)


Tim Keaton (Ph. D. Student at Depratment of Statistics)
Ji Hwan Oh (Ph. D., Department of Statistics)
Seokhun Bang (M. S., Department of Industrial Engineering)
Andres Nocolas Lopez (B. S. )


[1] H. Chun, M. H. Lee, S.-H. Kim and J. Oh (2018), Robust precision matrix estimation via weighted median regression with regularization, The Canadian Journal of Statistics, Accepted.

[2] J. Oh, F. Zhang, R. W. Doerge and H. Chun (2018), Kernel partial correlation: A novel approach to capturing conditional independence in graphical models for noisy data. Journal of Applied Statistics, Accepted.

[3]A.J. Kozik, C. H. Nakasu, H. Chun, Y.L. Jones-Hall (2017), Age, sex, and TNF associated differences in the gut microbiota of mice and their impact on acute TNBS colitis, Exp. Mol. Pathol., 103, 311-319.

[4] D. Ma, Y. Kim, B. Cooper, J. Oh, H. Chun, J. Choe, J. P. Schoonmaker, K. M. Ajuwon, B. Min (2017), Metabolomics profiling to determine the effect of postmortem aging on color and lipid oxidative stabilities of different bovine muscles, Journal of Agricultural and Food Chemistry, 65, 6708-6716.

[5] J. Shi, J. K. Knight, H. Chun, N. A. Guild, and J. M. Martil (2017), Using pre-assessment and in-class questions to change student understanding of molecular movements, Journal of Microbiology and Biology Education.

[6] H. Chun, M. H. Lee, J. Fleet and J. Oh (2016), Graphical models via joint quantile regression with component selection, Journal of Multivariate Analysis, 152, 162-171.

[7] H. Chun, X. Zhang and H. Zhao (2015), Gene regulation network inference with joint Gaussian graphical models, Journal of Computational and Graphical Statistics, 24(4), 954-974.

[8] B. Li, H. Chun and H. Zhao (2014), On an additive semi-graphoid model for statistical networks with application to pathway analysis, Journal of the American Statistical Association 109(507), 1188-1204.

[9] H. Chun, M. Chen, B. Li and H. Zhao (2013), Joint conditional Gaussian graphical models with multiple sources of genomic data, Frontiers in Genetics: Bioinformatics and Computational Biology 4:294.

[10] J. Moon and H. Chun (2013), Effective simultaneous confidence bands for repeated measurements in linear mixed-effect models, Journal of Statistical Computation and Simulation.

[11] B. Li, H. Chun and H. Zhao (2012), Sparse estimation of conditional graphical models with application to gene networks, Journal of the American Statistical Association, 107:152-167.

[12] H. Chun, D. Ballard, J. Cho and H. Zhao (2011), Association study with multiple markers and disease via sparse partial least squares, Genetic Epidemiology, 35:479-486.

[13] H. Chun, J. Kang, X. Zhang, M. Deng, H. Ma and H. Zhao (2011), Reverse engineering of gene regulation networks with an application to the DREAM4 in silico Network Challenge, Statistical Bioinformatics.

[14] S. H. Cho and H. Chun (2010),  Visualizing abnormal climate changes in central America from 1996-2000, Computational Statistics.

[15] H. Chun and S. Keles (2010), Simultaneous dimension reduction and variable selection with Sparse Partial Least Squares, Journal of Royal Statistical Society - Series B (Statistical Methodology), 72:3-25.

[16] H. Shim, H. Chun, C. D. Engelman and B. A. Payseur (2009), Genome-wide association studies using SNPs vs. haplotypes: An empirical comparison with data from the North American Rhematoid Arthritis Consortium, BMC Proceedings, 3 (Suppl 7):S35.

[17] H. Chun and S. Keles (2009), Expression quantitative loci mapping with sparse partial least squares, Genetics, 182:79-90.

[18] S. Keles and H. Chun (2008), Comments on: Augmenting Bootstrap to analyze high dimensional genomic data. Connections to the ridge regularized covariance estimator with bagging, TEST, 17(1): 36-39.

[19] P.F. Kuan, H. Chun and S. Keles (2008),  CMARRT: A tool for the analysis of ChIP-chip data from tiling arrays by incorporating the correlation structure. Pacific Symposium on Biocomputing, 13:515-526.

[20]Q. Gao, J. Cai, H. Cai, H. Chun, and T. Nantung, Risk-Based Percent Within Limits Specification for Acceptance Testing in Pavement Construction (Submitted).

[21] J. Cai, Q.Gao, H. Cai, H. Chun and T. Nantung, Optimal Sampling Strategy For Acceptance Decision in Highway Construction: A Cost-Benefit Analysis Approach. (Submitted).


''Collaborative Research: Semiparametric Conditional Graphical Models with Applications to Gene Network Analysis" (PI: Hyonho Chun), National Science Foundation (NSF). Project Period: 2011-2014.


Fall 2017 Applied Multivariate Analysis (STAT524)
Fall 2017 Statistical Theory (STAT417)

Spring 2017 Statistical methods (STAT511)

Spring 2016 Statistical theory (STAT417)
Fall 2015 Introduction to mathematical statistics (STAT528)

Spring 2015 Probability (STAT416)
Fall 2014 Introduction to mathematical statstics (STAT528)

Spring 2014 Introduction to mathematical statstics (STAT528)
Spring 2014 Statistical methods for biology (STAT503)
Fall 2013 Statistcal methods for biology (STAT503)

Spring 2013 Introduction to mathematical statistics (STAT528)
Fall 2012 Statistcal methods for biology (STAT503)

Spring 2012 Statistcal methods for biology (STAT503)
Fall 2011 Statistical methods for biology (STAT503)

Spring 2011 Statistical methods for high-throughput biological data (STAT598R)
Fall 2010 Statistcal methods for biology (STAT503)