Won Chang
Scholar

Won Chang

Google Scholar ID: Tz-VGIIAAAAJ
Associate Professor, Seoul National University
Uncertainty QuantificationComputer Model CalibrationSpatial StatisticsDeep Generative Models
Citations & Impact
All-time
Citations
759
 
H-index
15
 
i10-index
23
 
Publications
20
 
Co-authors
0
 
Contact
Resume (English only)
Academic Achievements
  • - Submitted papers: 'Stick-Breaking Mixture Normalizing Flows with Component-Wise Tail Adaptation for Variational Inference' and several others
  • - Accepted for publication: 'A Spatio-Temporal Dirichlet Process Mixture Model on Linear Networks for Crime Data' and several others
  • - Published papers: 'Dynamic Interactions of COVID-19 Incidences, Mobility, and Social Distancing Policies in Seoul: A VAR Model Approach' and several others
Research Experience
  • - Associate Professor, Department of Statistics, Seoul National University, Sep 2024 - present
  • - Associate Professor, Department of Mathematical Sciences, University of Cincinnati, July 2022 - Aug 2024
  • - Assistant Professor, Department of Mathematical Sciences, University of Cincinnati, August 2016 - June 2022
Education
  • - Postdoctoral Scholar, Department of Statistics, University of Chicago, August 2014 - July 2016 (mentored by Dr. Michael L. Stein and co-mentored by Dr. Elisabeth J. Moyer)
  • - Ph.D. in Statistics, Pennsylvania State University, 2014 (Thesis: Climate model calibration using high-dimensional and non-Gaussian spatial data; Advisors: Dr. Murali Haran and Dr. Klaus Keller)
  • - M.S. in Statistics, Korea University, 2009 (Thesis: Estimating volatility and distribution of European option prices using Bayesian UHF GARCH-M model; Advisor: Dr. Yousung Park)
  • - B.S. in Statistics, Korea University, 2007
Background
  • Research Interests: Uncertainty quantification for computer model experiments using deep learning and Gaussian processes, spatial data analysis for various fields of application including atmospheric science, hydrology, and genetics.
Co-authors
0 total
Co-authors: 0 (list not available)