Fei Lu

Fei Lu is an Associate Professor in the Department of Mathematics at Johns Hopkins University, affiliated with the Krieger School of Arts & Sciences. His research focuses on probability, statistics, and their applications in scientific computing, including stochastic modeling, data assimilation, and statistical inference. He holds a Ph.D. from the University of Kansas (2013), advised by David Nualart and Yaozhong Hu. Prior to JHU, he was a postdoctoral fellow at UC Berkeley and the Lawrence Berkeley National Laboratory under Alexandre Chorin.

Education:

• PhD in Mathematics, University of Kansas, 2013
• Postdoctoral Fellowship: UC Berkeley & Lawrence Berkeley National Laboratory

Research Interests:

• Malliavin Calculus and Stochastic PDEs
• Data-driven Stochastic Model Reduction
• Monte Carlo Methods and Data Assimilation
• Nonparametric Kernel Learning

His work bridges theoretical probability with computational methods, addressing challenges in complex systems modeling and uncertainty quantification.

Advising & Grants: While specific student names are not listed, his research group focuses on interdisciplinary projects in stochastic systems. Funding sources and grants are not explicitly detailed in the provided text.

Labs/Teams: Collaborations span applied mathematics, computational physics, and machine learning, though specific lab affiliations are not mentioned.