Hang Joon Kim

Hang Joon Kim

Assoc Professor

Associate Professor in Statistics and Undergraduate Program Director (Statistics)

French Hall

5410

A&S Mathematical Sciences - 0025

Education

B.A.: Yonsei University Seoul, Korea, 2002 (Business)

B.A.: Yonsei University Seoul, Korea, 2002 (Applied Statistics)

M.S.: Yonsei University Seoul, Korea, 2006 (Applied Statistics)

Ph.D.: The Ohio State University Columbus, OH, 2012 (Statistics)

Research and Practice Interests

Bayesian analysis; Statistical computing; Nonparametric Bayesian modeling
Missing data; Data privacy; Survey sampling
Computer experiment
Statistical genetics

Positions and Work Experience

2012 -2015 Postdoctoral Fellow, Duke University; National Institute of Statistical Science (NISS), Durham, NC

2015 -2021 Assistant Professor in Statistics, University of Cincinnati, OH

2018 -2020 ASA/NSF/Census Research Fellow, U.S. Census Bureau, Washington, DC

2019 -To Present Board of Directors, Korean International Statistical Society (KISS),

2021 -To Present Associate Professor in Statistics, University of Cincinnati,

2021 -To Present Faculty Fellow, NCSES Research Ambassadors Program, National Science Foundation (NSF),

Research Support

Charles Phelps Taft Research Center, Summer Research Fellowship, 2016, $8,000

U.S. Census Bureau, Summer at Census Scholar, 2017, $3,000

Grant: #YA132318AE0011 (extension #YA1333LB19P00000148), ASA/NSF/Census Research Fellowship, 04/30/2018-01/30/2020, Role:Principal Investigator, $170,379

Grant: #US Census Bureau 1333LB19P00000148 Investigators:Kim, Hang Joon 07-31-2019 -01-30-2020 US Census Bureau Hang Kim Census - additional funds to #1014103, COEUS proposal #9741 Role:PI $40,853.00 Completed Type:Grant

Grant: #Sub #60076671 / R01GM122078 01-13-2020 -05-01-2021 National Institute of General Medical Sciences Statistical Models for Genetic Studies, using Network and Integrative Analysis Role:PI $32,997.00 Completed Type:Grant

11-01-2021 -10-31-2024 Patient-Centered Outcomes Research Institute Mixed Data Meta-analysis: Integration of Individual Participant and Aggregate Data Role:PI $109,134 Active Type:Grant

Publications

Peer Reviewed Publications

Kim, H. J., Reiter, J. P., Wang, Q., Cox, L. H. and Karr, A. F. (2014. ) Multiple imputation of missing or faulty values under linear constraints .Journal of Business and Economics Statistics, , 32 ,375-386 (Published Article)

Kim, H. J., Karr, A. F. and Reiter, J. P. (2015. ) Statistical disclosure limitation in the presence of edit rules .Journal of Official Statistics, , 31 ,121-138 (Published Article)

Kim, H. J. and MacEachern, S. N. (2015. ) The generalized multiset sampler .Journal of Computational and Graphical Statistics, , 24 ,1134-1154 (Published Article)

Kim, H. J., Cox, L. H., Karr, A. F., Reiter, J. P., and Wang, Q. (2015. ) Simultaneous edit-imputation for continuous microdata .Journal of the American Statistical Association, , 110 ,987-999 (Published Article)

Park, M-J. and Kim, H. J. (2016. ) (Written in Korean), Statistical disclosure control for public microdata: present and future .Korean Journal of Applied Statistics, , 29 ,1041–1059 (Published Article) (Journal Site)

Chung, D., Kim, H. J., and Zhao, H. (2017. ) graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture .PLoS Computational Biology, , 13 ,(2): e1005388 (Published Article)

Kortemeier, E., Ramos, P. S., Hunt, K. J., Kim, H. J., Hardiman G., Chung D. (2018. ) ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets .PLoS ONE, , 13 ,(1): e0190949 (Published Article)

Kim, H. J., Reiter, J. P., and Karr, A. F. (2018. ) Simultaneous edit-imputation and disclosure limitation for business establishment data .Journal of Applied Statistics, , 45 ,63-82 (Published Article) (Accepted Manuscript)

Kim, H. J., Yu, Z., Lawson, A., Zhao H., and Chung, D. (2018. ) Improving SNP prioritization and pleiotropic architecture estimation by incorporating prior knowledge using graph-GPA .Bioinformatics, , 34 ,2139-2141 (Published Article)

Kim, H. J., Lu, B., Nehus, E. J., and Kim, M-O. (2019. ) Estimating heterogeneous treatment effects for latent subgroups in observational studies .Statistics in Medicine, , 38 ,339–353 (Published Article)

Hwang, Y., Kim, H. J., Chang, W., Yeo, K., and Kim, Y. (2019. ) Bayesian pollution source identification via an inverse physics model .Computational Statistics and Data Analysis, , 134 ,76–92 (Published Article)

Liu, X., Chen, A., Caicedo-Casso, A., Cui, G., Du, M., He, Q., Lim, L., Kim, H. J., Hong, C., and Liu, Y. (2019. ) FRQ-CK1 interaction determines the period of circadian rhythms in Neurospora .Nature Communications, , 10 ,4352 (Published Article)

Jung, Y., MacEachern, S. N., and Kim, H. J. (2020. ) Modified check loss for efficient estimation via model selection in quantile regression .Journal of Applied Statistics, , 48 ,866-886 (Published Article)

Kim, H. J., Drechsler, J., and Thompson, K. J. (2021. ) Synthetic microdata for establishment surveys under informative sampling .Journal of the Royal Statistical Society, Series A, , 184 ,255-281 (Published Article)

Khatiwada, A.,Wolf, B. J., Yilmaz, A. S., Ramos, P. S., Pietrzak, M., Lawson, A., Hunt, K. J., Kim, H. J., and Chung, D. (2022. ) GPA-Tree: Statistical approach for functional-annotation-tree-guided prioritization of GWAS results .Bioinformatics, , 38 ,1067-1074 (Published Article)

Hu, J., Drechsler, J. and Kim, H. J. (2022. ) Accuracy gains from privacy amplification through sampling for differential privacy .Journal of Survey Statistics and Methodology, , 10 ,688-719 (Published Article)

Thompson, K. J. and Kim, H. J. (2022. ) Incorporating economic conditions in synthetic microdata for business programs .Journal of Survey Statistics and Methodology, , 10 ,830-859 (Published Article)

Allen, C., Chang, Y., Neelon, B., Chang, W., Kim, H. J., Li, Z., Ma, Q. and Chung, D. (2022. ) A Bayesian multivariate mixture model for high throughput spatial transcriptomics .Biometrics, , (Published Article)

Deng, Q., Nam, J. H., Yilmaz, A. S., Chang, W., Pietrzak, M., Li, L., Kim, H. J.*, and Chung, D.* (2023. ) graph-GPA 2.0: Improving multi-disease genetic analysis with integration of functional annotation data .Frontiers in Genetics, , 14 ,(Published Article)

Chen, C., Bin, H., Kouril, M., Liu, J., Kim, H. J., and Sivaganesan, S. (2023. ) An application programming interface implementing Bayesian approaches for evaluating effect of time-varying treatment with R and Python .Frontiers in Computer Science, , 5 ,(Published Article)

Wang, Z., Kim, H. J., and Kim, H. J. (2023. ) Survey data integration for regression analysis using model calibration .Survey Methodology, , 49 ,(Published Article)

Zang, H., Kim, H. J.*, Huang, B., and Szczesniak, R. (2023. ) Bayesian causal inference for observational studies with missingness in covariates and outcomes .Biometrics, , (Published Article)

Book Chapter

Bakshi, B. R., Kim, H. J., and Goel, P. K. (2011 ) Using thermodynamics and statistics to improve the quality of life-cycle inventory data Thermodynamics and the Destruction of Resources .(pp. 235-248).Cambridge University Press

Technical Reports

Kim, H. J. and Karr, A. F. (2013. ) The effect of statistical disclosure limitation on parameter estimation for a finite population .Technical Report 183, National Institute of Statistical Sciences, Durham, NC, (Report)

Thompson, K. J., Kim, H. J., Bassel, N., Bembridge, K., Coleman, C., Freiman, M., Garcia, M., Kaputa, S., Riesz, S., Singer, P., Valentine, E, White, K. T. (2020. ) Final Report: Economic Census Synthetic Data Project Research Team .ADEP Working Paper Series ADEP-WP-2020-05, U.S. Census Bureau, Washington, DC, (Report)

Service

Joint Statistical Meetings (Session Chair, 2013/2017; Session Organizer, 2015 )

Biostatistics (Reviewer, Nov 2012 )

Journal of the American Statistical Association (Reviewer, Jun 2013, Mar 2018 )

Journal of Econometrics (Reviewer, Aug 2013 )

Computational Statistics and Data Analysis (Reviewer, Jun 2014, Feb/July/Dec 2015, May/Aug 2016, Jan/Mar/Jul/Oct 2017, Jan/June/Sep 2018, Feb 2019, May/Oct 2020 )

Journal of Official Statistics (Reviewer, Dec 2014, Jun 2016 )

Statistics and Probability Letters (Reviewer, Nov 2014, Sep 2015, Feb 2016 )

Bayesian Analysis (Reviewer, Oct 2015 )

Annals of Applied Statistics (Reviewer, Jan/Oct 2016, Dec 2017, Dec 2020 )

Journal of Survey Statistics and Methodology (Reviewer, Apr/Sep 2016, Feb/Sep 2017, Apr/June/Sep/Dec 2018, May/Oct 2019, Feb 2020 )

Sankhya B (Reviewer, Aug 2016 )

Statistical Analysis & Data Mining (Reviewer, Nov 2016 )

Journal of Privacy and Confidentiality (Reviewer, Dec 2016, Nov 2019 )

American Statistician (Reviewer, Jan 2017 )

Environmental Engineering Research (Reviewer, Apr 2017 )

Journal of Computational and Graphical Statistics (Reviewer, May 2017, Mar 2018 )

International Conference on Establishment Surveys (Student Contest Committee, 2015 )

American Statistical Association (SBSS Student Paper Competition Committee, 2016 )

Korean International Statistical Society (Career Development Award Committee, 2016; Student Paper Award Committee, 2018, 2020 )

BMC Medical Research Methodology (Reviewer, Sep 2018 )

National Science Foundation (Grant Proposal Review, Oct 2019 )