64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Statistical Modeling and Simulations with Applications in Climate and Environmental Science


Dr Emily Lei Kang


  • EK
    Dr Emily Lei Kang

  • MF
    Prof. Meredith Franklin
  • Spatial Uncertainty Quantification for Remote Sensing

  • BL
    Bo Li
  • Climate Model Evaluation using Sliced Elastic Distance

  • SS
    Steve Sain
  • Spatial statistics, extremes, and climate risk analytics

  • Category: Women in Statistics


    Statistical models and simulation methods have been providing solutions to various important scientific problems in climate and environmental science. This ISI Invited Session will showcase research projects involving innovative interactions between methodological development and scientific applications. This session brings together leading experts from three different sections of the research community: academics, industry and national laboratories. The speakers will present novel statistical methods motivated by significant scientific challenges to study climate change, impact to public health, environment studies and uncertainty quantification. Their presentations will feature various data settings arising from different application contexts in remote sensing, agriculture, public health and climate modeling. This will ensure that the main ideas in their talks will be of interest to statisticians and data scientists working in not methodological but also in applied and interdisciplinary fields.