معرفی
Jiajia Yu is a Phillip Griffiths Assistant Research Professor in the Department of Mathematics at Duke University, affiliated with the Trinity College of Arts & Sciences. She holds a Ph.D. in Mathematics from Rensselaer Polytechnic Institute (2023) and a B.S. in Mathematics and Applied Mathematics from Beijing Normal University (2017).
Her research focuses on applied and computational mathematics, with a particular emphasis on numerical methods for mean-field games, optimal transport, and inverse problems. She collaborates with prominent researchers such as Professors Hongkai Zhao, Xiuyuan Cheng, and Jian-Guo Liu.
Recent work includes convergence analysis of fictitious play in mean-field games, zeroth-order optimization methods, and bilevel optimization frameworks for inverse mean-field games. Her contributions span computational methods on manifolds and trajectory regularization in machine learning contexts.
Upcoming engagements include presentations at the IPAM Workshop on Scientific Machine Learning (2025) and Duke Math+ Program leadership on optimal transport topics. Her GitHub repositories showcase MATLAB implementations of FISTA algorithms and computational tools for mean-field games on manifolds.
