Mengyang Gu

CRML Affiliated Faculty

Assistant Professor, Statistics and Applied Probability

mengyang@pstat.ucsb.edu

website

Research

Mengyang is interested in probabilistic models of multiple time series, images, spatio-temporal data and functional data, with emphasis on scalar computation and theoretical properties. He developed computationally feasible methods and packages for emulating large-scale nonlinear partial differential equations (PDEs), inverse problem, dimension reduction and data fusion, with applications in quantifying uncertain geohazard, climate data and epigenetic studies.  He has research experience in Gaussian random field, Markov random field, latent factor models, stochastic differential equations and filtering algorithms for prediction and uncertainty quantification.  

Bio

Mengyang Gu joined the Department of Statistics and Applied Probability at the University of California, Santa Barbara as an assistant professor in 2019. Prior to this appointment, he received his bachelor's degree at Zhejiang University in 2012 and doctorate at Duke University in 2016. He worked as an assistant research professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University from 2016 to 2019.