Ph.D., Applied Mathematics and Scientific Computation, University of Maryland, College Park, MD, USA, 2017
B.Sc., Mathematics (First Honour), Chinese University of Hong Kong, Hong Kong, China, 2012
Professional Experience
2020 – Present: Assistant Professor of Data Science, Duke Kunshan University (DKU), responsible for teaching math and data science courses, and leading research projects
2017 – 2020: Postdoctoral Associate, Institute for Mathematics and its Applications, School of Mathematics, University of Minnesota, Twin Cities, MN, USA
Courses Taught
Undergraduate Foundation Courses: “Introductory Calculus”, “Calculus”
Interdisciplinary and Disciplinary Courses: “Principles of Machine Learning”, “Statistical Machine Learning”, ” Mathematics of Data Analysis and Machine Learning”
Undergraduate Electives: “Deep Learning”
Research Areas
Core Focus: Geometric deep learning with emphasis on geometry-aware data representation and graph-structured learning
Key Projects: Development of hyperbolic and non-Euclidean neural network frameworks; advancement of graph neural network methodologies for anomaly detection, generative modeling, and large-scale data analysis; scattering transform on manifolds
Interdisciplinary Exploration: Application of geometric machine learning techniques to biomedical imaging, industrial diagnostics, wireless communication systems, and cultural heritage analysis, bridging theoretical mathematics with real-world data-driven applications
Additional Information
Adjunct Professor, Wuhan University
Jiangsu Province “Shuangchuang” Award
Author of textbook “Lecture Notes in Deep Learning: Theoretical Insights into an Artificial Mind”
