I am currently pursuing an M.S. degree in Artificial Intelligence at the School of Artificial Intelligence and Computer Science, Jiangnan University, under the supervision of Rui Wang.
My research focuses on geometric deep learning and matrix/vector manifolds (such as SPD, Grassmann, correlation, and hyperbolic manifolds), and their applications in brain-computer interfaces.
I am expected to graduate in June 2026 and am currently seeking Ph.D. opportunities and research internships. If you are interested in me, feel free to contact me (chenhu-ml@163.com).
🔥 News
- 2025.04: 🎉🎉 Our paper “A Correlation Manifold Self-Attention Network for EEG Decoding” was accepted to IJCAI 2025!
- 2024.04: 🎉🎉 Our paper “A Grassmannian Manifold Self-Attention Network for Signal Classification” was published at IJCAI 2024!
📝 Publications
A Correlation Manifold Self-Attention Network for EEG Decoding
Chen Hu, Rui Wang, Xinyu Song, Tianyi Zhou, Xi Wu, Nicolas Sebe, Zhenan Chen
- First deep learning model on the manifold of full-rank correlation matrices.
- Extends Euclidean attention to the correlation manifold.
- Incorporates two permutation-invariant Riemannian metrics.
A Grassmannian Manifold Self-Attention Network for Signal Classification
Rui Wang, Chen Hu, Ziheng Chen, Xi Wu, Xinyu Song
- Extends Euclidean attention to Grassmannian manifolds.
- Builds a lightweight geometric deep learning network for spatiotemporal representations across Euclidean and Riemannian spaces.
🎖 Honors and Awards
- 🥇 2025.04: Postgraduate Research & Practice Innovation Program of Jiangsu Province – Principal Investigator
- 🥈 2024.08: Second Prize (Enterprise Track), National Finals of the 15th China College Students’ Innovation Competition
📖 Educations
- Jiangnan University, M.S. in Artificial Intelligence (09/2023 – Present)
- Hunan University of Technology and Business, B.E. in Data Science and Big Data Technology (09/2018 – 06/2022)