Welcome!
I am currently a Research Fellow in School of Mathematics and Statistics, University of Melbourne. I completed my Ph.D. in Mathematics from Tsinghua University, China, in 2021. See Haibo Li at the Mathematics Genealogy Project.
Research
I work on applied and computational mathematics. My research aims to build mathematical theory and design efficient algorithms for real-world challenges in science, engineering, and beyond. The research topics mainly include:
- Inverse problems
- Numerical linear algebra
- Scientific machine learning
I am always open to collaboration with researchers in mathematics, statistics, artificial intelligence, and related areas. For any discussions, please feel free to reach out to me by haibolee1729@gmail.com.
Useful Resources
- Courant Institute of Mathematical Sciences, NYU
- Institute for Pure and Applied Mathematics, UCLA
- Max-Planck-Institute for Mathematics in the Sciences
- Mathematical Research Institute of Oberwolfach
- Yau Mathematical Sciences Center, Tsinghua University
- What's new--Terence Tao's Blog
- Cosma Shalizi's Notebooks
News
15 Oct, 2025I gave a talk about 'Data-adaptive RKHS regularization for learning convolution kernels' at the Computational Neuroscience Lab at Monash University.
25 Sept, 2025I gave a talk about 'Projected Newton method for Bayesian inverse problems' in the Applied Mathematics Seminar at University of Melbourne.
9 Aug, 2025My paper on 'Krylov methods for LSE problems' was published online on Numerical Algorithms. Check it out!