Bonjour!
Associate Professor ยท Sun Yat-sen University
Mathematics, data-driven learning, and interdisciplinary AI.
Hello and welcome. I am an Associate Professor in the Department of Mathematics, Zhuhai at Sun Yat-sen University. This site is where I collect research, talks, and selected projects across applied mathematics, machine learning, and interdisciplinary data analysis.
Main Research Interests
My work centers on turning theory-rich problems into practical learning systems: interpretable models, robust training under imperfect data, and AI methods shaped by scientific or mathematical structure rather than raw data alone.
Interpretable models under noisy labels
I study robust learning strategies for affective computing from EEG data, especially when supervision is noisy and explainability matters.
Medical data and image analysis
I develop AI methods for clinically meaningful problems, with an emphasis on medical images, registration, and learning from imperfect annotations.
Scientific systems guided by domain knowledge
I am interested in machine learning pipelines that respect physics, chemistry, and other scientific constraints instead of treating every problem as a black box.
Learning methods that serve mathematics
I also explore how machine learning can support mathematical structures and dynamical systems, including work related to Koopman-inspired modeling.
A place to keep exploring
If you are visiting for the first time, the best entry points are my publications, talks, and code on GitHub. If your interests overlap with robust learning, AI for scientific or medical problems, or applied mathematics, feel free to get in touch.
I am not an active blogger, but I do try to keep this site useful: a compact record of what I work on, where ideas came from, and where you can dig deeper.
From hometown curiosity to interdisciplinary research
The path has moved through mathematics, scientific computing, machine learning, and collaborations across health and industry. These snapshots make that progression easier to read at a glance.
Recent postdoc at the Oden Institute
My most recent postdoc was at the Oden Institute for Computational Engineering and Sciences, supervised by Dr. Craig Michoski. I developed data-driven and deep learning methods for interdisciplinary applications, and part of that work later evolved into solutions and services at Sophelio.
Ottawa and Southern Utah
Before that, I was a postdoc in the Data Science and Machine Learning group at the Department of Mathematics and Statistics, University of Ottawa, after a year as a visiting assistant professor at Southern Utah University.
PhD at the University of Wyoming
I received my PhD in Applied Mathematics from the University of Wyoming, working on particle methods for Euler-Poincare equations under Prof. Long Lee. Collaborations with Prof. Roberto Camassa helped push my interests toward data science and machine learning.
Mathematics training at USTC
I earned my bachelor's degree in Mathematics from the University of Science and Technology of China, where I worked on two-dimensional integration methods with Prof. Jiansong Deng.
Early inspiration in Fujian
I was born in a small town called Jiyang in Fujian Province, China. My days in high school, together with clubs, competitions, and inspiring teachers, shaped my broad curiosity about science and mathematics.
A personal note
My name comes from the first characters of my parents' first job locations. It is a small reminder that even under practical constraints, there is room to shape life with imagination and intention.