Won Chang

Won Chang , Ph.D. in Statistics

Asst Professor

Assistant Professor in Statistics

Office
5516 French Hall
2815 Commons Way
Cincinnati, Ohio 45221
Phone 513-556-4069
Email changwn@ucmail.uc.edu

Professional Summary

personal webpage: http://wonchang.net

 My current research focuses on resolving "big data'' issues in uncertainty quantification and spatial modeling for environmental research and business analytics. My methodological work pertains developing new computationally efficient approaches to analyzing large data sets with complex dependence structures and distributional properties for which traditional methods are not scalable.

Education

Ph.D. : Pennsylvania State University University Park, 2014 (Statistics)

M.S.: Korea University Seoul, 2009 (Statistics)

B.S.: Korea University Seoul, 2007 (Statistics)

Research and Practice Interests

High-dimensional spatial data analysis, Non-Gaussian spatial data analysis, Data-driven simulation of climate processes, Computer model emulation and calibration, Composite likelihood, Statistical methods in environmental science, Bayesian inference, Time series

Research Support

Grant: #1000006747/GR#127836(R21HG012482) Investigators:Chang, Won 06-01-2022 -05-31-2024 National Human Genome Research Institute Statistical Power Calculation Framework for Spatially Resolved Transcriptomics Experiments Role:PI 12563.00 Hold Level:Federal

Publications

Peer Reviewed Publications

Park, J., Chang, W., Choi, B. (2022. ) An interaction Neyman-Scott point process model for Coronavirus Disease-19 .Spatial Statistics, , 47 ,100561

Bhatnagar, S., Chang, W., Kim., S., Wang, J. (2022. ) Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression .SIAM/ASA Journal on Uncertainty Quantification, , 10 (1 ) ,1

Chang, W., Konomi, B. A., Karagiannis, G., Guan, Y., Haran, M. (2022. ) Ice model calibration using semi-continuous spatial data .the Annals of Applied Statistics, ,

Kim, S., DeSarbo, W., and Chang, W. (2021. ) Note: A new approach to the modeling of spatially dependent and heterogeneous geographical regions .International Journal of Research in Marketing, , 38 (3 ) ,792

Plumlee, M., Asher, T. G., Chang, W., Bilskie, M. (2021. ) High-fidelity hurricane surge forecasting using emulation and sequential experiments .the Annals of Applied Statistics, , 15 (1 ) ,460

Wang, J., Liu, Z., Foster, I., Chang, W., Kettimuthu, R., Kotamarthi, R. (2021. ) Fast and accurate learned multiresolution dynamical downscaling for precipitation .Geoscientific Model Development, , 14 (10 ) ,6355

Tracy, J., Chang, W., Freeman, S., Brown, C., Palma, A., Ray, P. (2021. ) Enabling Dynamic Emulation of High-Dimensional Model Outputs: Demonstration for Mexico City Groundwater Management .Environmental Modelling & Software, , 147 ,105238

Chang, W., Kim, S., Chae, H. (2020. ) A regularized spatial market segmentation method with Dirichlet process Gaussian mixture prior .Spatial Statistics, , 30 ,100402

Chang, W., Wang, J., Marohnic, J., Kotamarthi, V.R., and Moyer, E. J. (2020. ) Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking .Climate Dynamics, , 55 ,175

Olson, R., An, S.-I., Fan, Y., Chang, W., Evans, J. P., & Lee, J.-Y. (2019. ) A novel method to test non-exclusive hypotheses applied to Arctic ice projections from dependent models .Nature Communications, , 10 (1 ) ,3016

Guan, Y., Sampson, C., Tucker, D., Chang, W., Mondal, A., Haran, M., Sulsky, D. (2019. ) Computer model calibration based on image warping metrics: an application for sea ice deformation .the Journal of Agricultural, Biological and Environmental Statistics, , 24 (3 ) ,444

Chang, W., and Xi, C. (2018. ) Monthly Rainfall-Runoff Modeling at Watershed Scale: A Comparative Study of Data-Driven and Theory-Driven Approaches .Water, , 10 (9 ) ,1116

Olson, R., Ruckert, K. L., Chang, W., Keller, K., Haran, M., and An, S.-I. (2018. ) Stilt: easy emulation of AR(1) computer model output in multidimensional parameter space .the R journal, , 10 (2 ) ,209

Hwang, Y., Kim, H.J., Chang, W., Yeo, K., Kim., Y. (2018. ) Bayesian pollution source identification via an inverse physics model .Computational Statistics & Data Analysis, , 134 (76 ) ,

Haran, M., Chang, W., Keller, K., Nicholas, R., and Pollard, D. (2017. ) Statistics and the Future of the Antarctic Ice Sheet .Chance, , 30 (4 ) ,37

Chang, W., Haran, M., Applegate, P.J., and Pollard, D. (2016. ) Calibrating an ice sheet model using high-dimensional binary spatial data .Journal of the American Statistical Association, , 111 (513 ) ,57

Pollard, D., Chang, W., Haran, M., Applegate, P., and DeConto, R. (2016. ) Large ensemble modeling of last deglacial retreat of the West Antarctic Ice Sheet: Comparison of simple and advanced statistical techniques .Geoscientific Model Development, , 9 ,1697

Jeon, S., Chang, W., and Park, Y. (2016. ) An option pricing model using high frequency data .Procedia Computer Science, , 91 ,175

Chang, W., Haran, M., Applegate, P.J., and Pollard, D. (2016. ) Improving ice sheet model calibration using paleoclimate and modern data .the Annals of Applied Statistics, , 10 (4 ) ,2274

Chang, W., Stein, M. L., Wang, J., Kotamarthi, V. R., and Moyer, E. J. (2016. ) Changes in spatio-temporal precipitation patterns in changing climate conditions .Journal of Climate, , 29 (23 ) ,8355

Chang, W., Haran, M., Olson, R., and Keller, K. (2015. ) A composite likelihood approach to computer model calibration with high-dimensional spatial data .Statistica Sinica, , 25 (1 ) ,243

Chang, W., Applegate, P.J., Haran, M. and Keller, K. (2014. ) Probabilistic calibration of a Greenland Ice Sheet model using spatially-resolved synthetic observations: toward projections of ice mass loss with uncertainties .Geoscientific Model Development, , 7 ,1933

Chang, W., Haran, M., Olson, R., and Keller, K. (2014. ) Fast dimension-reduced climate model calibration and the effect of data aggregation .the Annals of Applied Statistics, , 8 (2 ) ,649

Olson, R., Sriver, R., Chang, W., Haran, M., Urban, N.M., and Keller, K. (2013. ) What is the effect of unresolved internal climate variability on climate sensitivity estimates? .Journal of Geophysical Research - Atmospheres, , 118 (10 ) ,4348

Presentations

Invited Presentations

Won Chang (10-2021. ) Bayesian Model Calibration and Sensitivity Analysis for Oscillating Biological Experiments .Department of Biostatistics, University of Louisville, Louisville, KY. Level:Department

Won Chang (06-2021. ) New Statistical Framework for Large Scale Computer Model Calibration Using Deep Learning .Ecosta 2021, Hong Kong. Level:International

Won Chang (05-2021. ) Statistical Inference with Neural Network Imputation for Item Nonresponse .Department of Statistics, Korea University, Seoul. Level:Department

Won Chang (03-2021. ) Computer Model Emulation and Calibration Using Complex Spatial and Temporal Data .Department of Statistics, Yonsei University, Seoul. Level:Department

Won Chang (12-2020. ) Computer Model Emulation and Calibration Using Complex Spatial and Temporal Data .LANL Stats Seminar, Los Alamos National Laboratory, NM. Level:Prof. Org.

Won Chang (11-2020. ) Computer Model Emulation and Calibration Using Complex Spatial and Temporal Data .Departmental Colloquium, Department of Statistics, University of Illinois, Urbana-Champaign, IL. Level:Department

Ice Model Calibration Using Semi-continuous Spatial Data (10-2020. ) Statistics Colloquium, Department of Mathematics and Statistics, University of Maryland, Baltimore County, MD. Level:Department

Won Chang (09-2020. ) Ice Model Calibration Using Semi-continuous Spatial Data .UC Day at JPL, NASA Jet Propulsion Laboratory, CA. Level:Prof. Org.

Won Chang (10-2019. ) Ice Model Calibration using Semi-continuous Spatial Data .ICOSDA 2019, Grand Rapids, MI. Level:National

Won Chang (10-2019. ) Ice Model Calibration using Semi-continuous Spatial Data . Department of Statistics, Ohio State University, Columbus, OH. Level:Department

Won Chang (08-2019. ) New Statistical Framework for Large Scale Computer Model Calibration Using Deep Learning .SAMSI Deep Learning Workshop, Research Triangle Park, NC. Level:National

Won Chang (05-2019. ) Ice Model Calibration using Zero-Inflated Continuous Spatial Data .SAMSI MUMS Closing Workshop, Research Triangle Park, NC. Level:National

Won Chang (11-2018. ) ‘Bit Data’ Challenges in Uncertainty Quantification and Environmental Statistics .Department of Physics, University of Dayton, Dayton, OH. Level:Department

Won Chang (08-2018. ) Computer Model Emulation and Calibration using High-dimensional and Non-Gaussian Spatial Data .SAMSI MUMS Opening Workshop, Research Triangle Park, NC. Level:National

Won Chang (07-2018. ) A Bayesian Spatial Market Segmentation Method Using Dirichlet Process Gaussian Mixture Model and LASSO regularization .ISBA-EAC, Seoul, Korea. Level:International

Won Chang (07-2018. ) Computer Model Emulation and Calibration using High-dimensional and Non-Gaussian Spatial Data .Young Statistician's Meeting, Yangpyeong, Korea. Level:National

Won Chang (06-2018. ) A Bayesian spatial market segmentation method using Dirichlet process-Gaussian mixture models .Ecosta 2018, Hong Kong. Level:International

Won Chang (06-2018. ) Calibrating an ice sheet model using high-dimensional binary spatial data .IMS-APRM, Singapore. Level:International

Won Chang (05-2018. ) Ice Model Calibration using Zero-Inflated Continuous Spatial Data .SAMSI CLIM Transition Workshop, Research Triangle Park, NC. Level:National

Won Chang (12-2017. ) Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking .Department of Atmospheric Sciences, University of Illinois, Champaign, IL. Level:Department

Won Chang (12-2017. ) Changes in Spatio-temporal Precipitation Patterns in Changing Climate Conditions .IISA International Conference on Statistics 2017, Hyderabad, India. Level:International

Won Chang (11-2017. ) Calibrating an ice sheet model using high-dimensional binary spatial data .Department of Mathematics and Statistics, University of North Carolina, Charlotte, NC. Level:Department

Won Chang (08-2017. ) Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking .SAMSI Mathematical and Statistical Methods for Climate and Earth Systems Program Opening Workshop, Durham, NC. Level:National

Won Chang (05-2017. ) Calibrating an ice sheet model using high-dimensional binary spatial data .Korean Statistical Society Spring Meeting 2017, Seoul, Korea. Level:International

Won Chang (02-2017. ) Improving ice sheet model calibration using paleoclimate and modern data .Department of Geography, University of Cincinnati, Cincinnati, Cincinnati, OH. Level:Department

Won Chang (01-2017. ) Improving ice sheet model calibration using paleoclimate and modern data .Korean National Institute for Mathematical Sciences, Daejeon, Korea. Level:International

Won Chang (11-2016. ) Calibrating an ice sheet model using high-dimensional binary spatial data .University of Akron, Department of Statistics, Akron, OH. Level:Department

Poster Presentations

Won Chang (12-2018. ) New Statistical Framework for Large Scale Computer Model Calibration Using Deep Learning .AGU 2018 Fall Meeting, Washington DC. . Level:National

Won Chang (12-2017. ) Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking .AGU 2017 Fall Meeting, New Orleans, LA. . Level:National

Paper Presentations

Won Chang (08-2018. ) Changes in Spatiotemporal Precipitation Patterns in Changing Climate Conditions .Vancouver, BC. Conference. Level:International

Won Chang (07-2017. ) Improving ice sheet model calibration using paleoclimate and modern data .Lancaster, UK. Conference. Level:International

Won Chang Improving ice sheet model calibration using paleoclimate and modern data .Hong Kong. Conference. Level:International

Honors and Awards

04-2021 Elected Member, International Statistical Institute (ISI)

Post Graduate Training and Education

08-2014-07-2016 Postdoctoral Scholar, (with Dr. Michael Stein and Dr. Elisabeth Moyer) , University of Chicago, , Chicago

Contact Information

Academic - Office
5516 French Hall
Cincinnati  Ohio, 45221
Phone: 513-556-4069
changwn@ucmail.uc.edu