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Won Chang

Title: Assistant Professor in Statistics
Office: 5516 French Hall
Tel: 513-556-4069
Email: changwn@ucmail.uc.edu
Web: http://www.wonchang.net/

  • My current research focuses on resolving "big data'' issues in uncertainty quantification and spatial modeling for environmental research and business analytics. The key topics of my recent methodological work include
    • Analysis of high-dimensiolnal non-Gaussian spatial data
    • Computer model calibration using dimension reduction, Gaussian processes, and deep learning
    • Spatial modeling for marketing analysis using variable selection and Dirichlet processes
    • Image component analysis for spatio-temporal pattern of precipitation in high resolution climate models and observational data

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 Information

Research 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

Publications

Peer-reviewed Publications

  • 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.
  • Jeon, S., Chang, W., Park, Y. (2016). An Option Pricing Model using High Frequency Data. Procedia Computer Science, 91, 175.
  • Chang, W., Stein, M. L., Jiali, W., 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., Applegate, P.J., Pollard, D. (2016). Calibrating an ice sheet model using high-dimensional binary spatial data. Journal of the American Statistical Association, 111 (513), 57.
  • Chang, W., Haran, M., Applegate, P.J., Pollard, D. (2016). Improving ice sheet model calibration using paleoclimate and modern data. the Annals of Applied Statistics, 10 (4), 2274.
  • Pollard, D., Chang, W., Haran, M., Applegate, P., and DeConto, R. (2015). Large ensemble modeling of last deglacial retreat of the West Antarctic Ice Sheet: Comparison of simple and advanced statistical techniques. Geoscientific Model Developement, 9, 1697.
  • 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), 243-260.
  • 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), 649-673.
  • 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, 1933-1943 .
  • Olson, R., Sriver, R., Chang, W., Haran, M., Urban, N.M., Keller, K. (2013). What is the effect of unresolved internal climate variability on climate sensitivity estimates?. Journal of Geophysical Research - Atmospheres, 118 (10), 4348-4358.

Presentations & Lectures

Invited Presentations

  • 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.
  • Won Chang (12-2017). Changes in Spatio-temporal Precipitation Patterns in Changing Climate Conditions IISA International Conference on Statistics 2017, Hyderabad, India.
  • 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.
  • 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.
  • Won Chang (05-2017). Calibrating an ice sheet model using high-dimensional binary spatial data Korean Statistical Society Spring Meeting 2017, Seoul, Korea.
  • Won Chang (02-2017). Improving ice sheet model calibration using paleoclimate and modern data Department of Geography, University of Cincinnati, Cincinnati, Cincinnati, OH.
  • Won Chang (01-2017). Improving ice sheet model calibration using paleoclimate and modern data Korean National Institute for Mathematical Sciences, Daejeon, Korea.
  • Won Chang (11-2016). Calibrating an ice sheet model using high-dimensional binary spatial data University of Akron, Department of Statistics, Akron, OH.

Paper Presentations

  • Won Chang (07-2017). Improving ice sheet model calibration using paleoclimate and modern data, Lancaster, UK.
  • Won Chang Improving ice sheet model calibration using paleoclimate and modern data, Hong Kong.

Poster Presentations

  • 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.

Experience & Service

Post Graduate training and Education

  • 08-2014 to 07-2016, Postdoctoral Scholar, University of Chicago, Chicago.
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