Rate My Professor Han Gan

Gan's research focuses on probability theory, utilizing Stein's method to develop approximations for equilibrium distributions in stochastic models including Cannings models with mutation, Wright-Fisher models, Poisson-Dirichlet processes, and two-island seed-bank models, with applications to genomics and random permutations. Key publications include 'Dirichlet approximation of equilibrium distributions in Cannings models with mutation' (Advances in Applied Probability, 2017), 'Stein factors for negative binomial approximation in Wasserstein distance' (2015), 'Stein’s method for the Poisson–Dirichlet distribution and the Ewens sampling formula, with applications to Wright–Fisher models' (2021), and 'Arcsine laws for random walks generated from random permutations with applications to genomics' (Journal of Applied Probability, 2021). He contributes to interdisciplinary health research, including COVID-19 inequities modeling, diabetes care impact studies, and evaluations of continuous glucose monitoring equity, supported by Health Research Council of New Zealand funding. Gan leads statistical consulting via Te Ara Tatauranga and organizes sessions on probability and mathematical statistics at international conferences.