Dr. Junyang Wang

Biography

Junyang Wang is a researcher in Computational Statistics, focusing on Bayesian methodology. His research interests include Bayesian Computation, Probabilistic Numerics, Variational Inference, and applications of Bayesian methodology in sustainability and public health. He is currently working with Dr. Sarah Filippi to develop scalable Bayesian mixture models using variational inference on mixed data, motivated by the application of clustering risk factor data to identify useful phenotypes. He is also collaborating with the NCD-RisC project, focusing on various application aspects of his work. Previously, Junyang worked as a Postdoctoral Research Associate in the Department of Civil and Environmental Engineering at Imperial College London on an interdisciplinary project that developed Bayesian statistical methodologies for material flow analysis (MFA). He completed his PhD in Statistics at Newcastle University, specializing in Bayesian Probabilistic Numerical Methods for Ordinary Partial Differential Equations under the supervision of Professor Chris Oates. Additionally, Junyang earned his undergraduate degree in Mathematics from the University of Cambridge.

Research Interests