Shozen, originally from Tokyo, pursued his studies in statistics and machine learning at Keio University and later at UC Davis. Advancing his education, he completed his master’s at Imperial College London. His thesis proposed a new method to estimate human contact intensity which utilized new approximation techniques for non-parametric Bayesian inference. Beyond his formal education, Shozen spent three years collaborating with Stanford’s medical school, contributing to public health research. At StatML, he aims to become an expert in Bayesian statistical modelling and computation, with aspirations to apply novel techniques in studying human contact patterns and their impact on infectious disease spread
Shozen Dan
