Prof. Castruccio obtained his PhD at the University of Chicago (USA), and has worked in Saudi Arabia and the United Kingdom before his current appointment as Associate Professor at the University of Notre Dame (USA). His main area of research focuses on the development of spatio-temporal statistical models for environmental applications, with applications spanning from assessment of renewable energy resources to assessing mortality from air pollution. His focus is mostly on climate and weather modes, and the use of statistical and machine learning models that can act as a stochastic approximation to provide a computationally affordable assessment of parameter sensitivity analysis. His methodological research is focused on the development of non-stationary Gaussian processes in Euclidean and spherical domains, and in scalable multi-resolution inference for high-dimensional processes in space and time.

Dr. Jian Kang is a Professor in the Department of Biostatistics at the University of Michigan. He received his PhD in Biostatistics from the University of Michigan in 2011. He was an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Radiology and Imaging Sciences at Emory University from 2011- 2015. His main research interests are developing statistical methods and theory for large-scale complex biomedical data analysis with focuses on Bayesian approaches, imaging statistics and bioinformatics. He has co-authored over 110 publications in statistical journals and medical journals. Dr. Kang currently serves as the Associate Editor of Annals of Applied Statistics, Biometrics, The New England Journal of Statistics in Data Science and Statistics in Medicine. Dr. Kang was elected as the Fellow of the American Statistical Association in 2021.