ABOUT ME

My previous research mainly focuses on data-driven turbulence modeling by using Bayesian inference and machine learning techniques. More recently, I also started to explore generative learning techniques (e.g. generative adversarial networks) to emulate and predict PDE-governed systems.

 

In general, my research interests lie in an interdisciplinary area of computational physics, applied mathematics and statistics.

EDUCATION

RESEARCH EXPERIENCES

2014 - 2018

Virginia Tech, United States

Ph.D., Aerospace Engineering

2011 - 2014

Southeast University, China

M.S., Power Engineering

2007 - 2011

Southeast University, China

B.S., Thermal Energy and Power Engineering

01/2019 -

Computing + Mathematical Sciences, Caltech

Geological and Planetary Sciences, Caltech

Postdoctoral Researcher

09/2018 - 12/2018

Institute for Pure and Applied Mathematics, UCLA

Visiting Scholar

05/2018 - 08/2018

Lawrence Berkeley National Laboratory

Summer Intern

06/2016 - 07/2016

Center for Turbulence Research, Stanford University

Visiting Graduate Student

Climate Modeling Alliance (CliMA)

MC C1-221, Pasadena, CA 91125

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