Academic Background
My undergraduate major is information and computing science at math department. It might not be a common major, but basically it is just the combination of pure math and computing math. I have taken numerous pure math courses, including differential manifolds, abstract algebra, group representation, harmonic analysis, advanced PDE (Evans’ book part 2), etc. I may not take any further pure math course in the future, unless it is necessary for my research.
I am also proficient in programming. I am maintaining my blog running on my own server. You can click on the “Blog” on the left to visit it. If the website crashes, usually it means that I am trying to add some new features and it blows up :(. My favorite language is python, then wolfram mathematica. The former is easy to use and the latter is amazing at symbolic computations. I use matlab or c++ only if it is necessary.
Below is the list of my research projects (non-course projects). You can find the corresponding codes on my Github website. Repositories will be public after their final versions are pushed with proper README documents.
Research Projects
Explainable and Robust Graph Neural Network for Spatio-Temporal Prediction
- Mentor: Prof. Xuan Di, Zhaobin Mo
- Columbia University
- A paper has been accepted by 2024 IEEE Conference on Intelligent Transportation Systems (ITSC 2024)
- A paper will be submitted to 2025 International Conference on Very Large Data Bases (VLDB 2025).
- A paper can be expected to be submitted to AAAI conference in 2025.
Singular Value Decomposition in Machine Learning
- Mentor: Prof. Chunguang Xiong
- Beijing Institute of Technology
- Undergraduate Thesis