Fangyuan Yu is a Ph.D. student in the Statistics program at KAUST, his supervisor is Professor Ajay Jasra.

Education and Early Career

Fangyuan holds a master degree of statistics in National University of Singapore (NUS). He also holds a master degree and a bachelor degree of mathematics and applied mathematics in Shandong University, China.

Before joining KAUST, Fangyuan worked as a research assistant in Department of Statistics and Applied Probability, National University of Singapore from August 2018 to July 2019. His principal investigator was Professor Ajay Jasra.

Research Interest

His main areas of research are computational probability, Bayesian Inference, Monte Carlo methodology, Stochastic filtering, MCMC methodology and Recursive Neural Network

Preprints

(2018) Jasra, A. & Yu F. CLTs for coupled particle filters

(2019) Jasra, A., Yu, F. & Heng, J. MLPF for filtering in continuous time.

(2020) Jasra, A., Law KJH & Yu F. Unbiased Filtering of a Class of Partially Observed Diffusions.