Shangyang Li

Postdoc researcher

Email:lishangyang@@gdiist.cn

Personal Biography:

Graduated with a bachelor's degree in Physics from Beijing Normal University in 2019 and earned a PhD from the Academy for Advanced Interdisciplinary Studies at Peking University in 2024. Research focuses on computational neuroscience and machine learning, exploring brain information processing principles through computational modeling, understanding mechanisms of neurological diseases, and investigating machine learning algorithms. Emphasizes large-model technology and developing neuromedical large models tailored to the neuro-medicine field. Published several academic papers and serves as a reviewer for neuroscience journals and international machine learning conferences.

Research Fields：

Computational Neuroscience and Machine Learning

Representative Papers:

[1] Spindle oscillation emerges at the critical state of the electrically coupled network in thalamic reticular nucleus (Shangyang Li, Chaoming Wang and Si Wu) (Cell Reports 2024)

[2] Graph Adversarial Contrastive Learning (Jiayan Guo*, Shangyang Li*, Yue Zhao and Yan Zhang) （DASFAA 2022，Co-first author and corresponding author，CCF-B）

[3] An Information Theoretic Perspective for Heterogeneous Subgraph Federated Learning (Jiayan Guo*, Shangyang Li* and Yan Zhang) （DASFAA 2023，Co-first author and sole corresponding author，CCF-B）

[4] BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming（Chaoming Wang, Tianqiu Zhang, Xiaoyu Chen, Sichao He, Shangyang Li and Si Wu) (eLife 2024)

[5] BrainPy: a differentiable brain simulator bridging brain simulation and brain-inspired computing （Chaoming Wang, Tianqiu Zhang, Hongyaoxing Gu, Sichao He, Shangyang Li and Si Wu) (ICLR 2024)