Applied and Computational Math
English, Mandarin, Sichuanese
Julia, Python, MATLAB, LaTeX
Academically, I am interested in intellectual mathematical research synergizing computation and inference. My current work is centered around probabilistic inference, numerical algorithms, and multiscale methods for scientific computing and machine learning in physics and data science.
I am very grateful to be supported by the Kortschak Scholars Program.
Ph.D. in Applied and Computational Mathematics, 2018-2023(expected)
Department of Computational and Mathematical Sciences, Caltech
B.S. in Pure and Applied Mathematics, 2014-2018
Department of Mathematical Sciences, Tsinghua University
- I am co-organizing the minisymposium Recent Advances in Kernel Methods for Computing and Learning in SIAM Mathematics of Data Science, San Diego, Sep 26-30, 2022.
- I gave a talk at SOCAMS in May 21, 2022. [Slide]
- I did my candidacy talk. [Slide]
- I gave a talk at the Rough Path Interest Group in April 28, 2022. [Slide]
- Gave a talk in SIAM Uncertainty Quantification (UQ22) Minisymposium of New Developments in Gaussian Processes, Atlanta, April 12-15, 2022. [Slide]
- I gave a talk in the CMX student seminar on "Multiscale Computation and Parameter Learning for Kernels from PDEs: Two Provable Examples", Nov 2020. [Slide]
- I gave a talk in the session of Kernel Methods at the Second Symposium on Machine Learning and Dynamical Systems, Fields Institute, Sep 21-25, 2020. See this YouTube Channel. [Slide]
- I gave a talk on "Consistency of Hiearchical Parameter Learning" at the Bernoulli-IMS One World Symposium, Aug 2020. Check this YouTube Channel. [Slide]