👋 About Me
I am a computational neuroscientist and AI researcher at the Montreal Neurological Institute, McGill University（Supervised by Prof. Sylvain Baillet）. My research focuses on understanding the spatiotemporal dynamics of human brain activity, with applications in computational psychiatry, neuro-AI, and brain-computer interfaces.
My PhD thesis investigates the spatiotemporal structure of human spontaneous traveling waves in the brain. I combine advanced neuroimaging techniques (MEG, EEG, fMRI) with computational modeling and deep learning to uncover fundamental principles of brain dynamics and their alterations in psychiatric disorders.
Previously, I earned my Master's degree in Biomedical Engineering at UESTC under Prof. Dezhong Yao, and my Bachelor's in Automation at HuaQiao University.
My research framework encompasses three core interdisciplinary domains: computational neuroscience, computational psychiatry, and neuro-AI. By integrating the biomedical foundations of brain science and mental health with computational techniques in modeling, theory, and tool design, I am dedicated to reverse-engineering brain mechanisms to build intelligent systems, exploring neural circuit function modeling, computational diagnosis and treatment of psychiatric disorders, and brain-inspired AI architecture design.
I am now a postdoc researcher, collaborating with Prof. Ben Fulcher, Prof. James M. Shine, and Prof. Joseph Lizier on interdisciplinary projects integrating neurophysics, complex systems, information dynamics, and computational neuroscience. This collaboration extends my previous work on spatiotemporal cortical waves, MEG/fMRI-based brain dynamics, cortical gradients, and psychiatric/neurodevelopmental disorders by introducing advanced time-series analysis, information-theoretic measures, and complex-network modeling to characterize how large-scale neural activity supports cognition, arousal, and brain health. The work builds on my doctoral research on spontaneous human brain activity and my broader experience in multimodal neuroimaging, machine learning, and computational modeling.
🏆 Representative works:
1. Hierarchical Flows of Human Cortical Activity
3. MLE toolbox
4. The Cortical Temporal Axis: MEG-Based Cross-Frequency Gradients with Biological Anchors
