I am currently an Assistant Professor at School of Computer Science, Peking University, dedicated to exploring the computational principles of the brain. I view the brain as an intricate computer with complex dynamics that offers profound insights for the development of brain-inspired and brain-like computing frameworks.

In my previous role as a postdoctoral researcher with Prof. Wolfgang Maass (the father of spiking neural network and brain-like computation) at Institute of Theoretical Computer Science, Graz University of Technology, I delved into brain-like computation and computational neuroscience. Before that, my doctoral research, conducted at School of Physics, the University of Sydney with Prof. Pulin Gong, focused on neurophysics, an interdisciplinary field bridging physics and neuroscience.

Research Interest

My primary research interest lies in unraveling the computational principles of the brain, with a specific focus on elucidating the link between the brain’s structure, encompassing both its physiology and dynamics, and its computational functions. The intersection of computing, neuroscience and physics serves as my playground.

In addition, my research interest extends to showcasing the remarkable capabilities of the brain in brain-inspired and brain-like intelligent systems, specifically in areas like autonomous driving and robotics.

Hiring info

I am currently looking for talented PhD and undergraduate intern students to start my lab. Please see more at Job Opportunities.

Selected Publications

1. Chen, Guozhang, Franz Scherr, and Wolfgang Maass. “Data-based large-scale models provide a window into the organization of cortical computations.” bioRxiv (2023): 2023-04.

2. Chen, Guozhang, Franz Scherr, and Wolfgang Maass. “A data-based large-scale model for primary visual cortex enables brain-like robust and versatile visual processing.” Science Advances 8.44 (2022): eabq7592.

3. Chen, Guozhang, and Pulin Gong. “A spatiotemporal mechanism of visual attention: Superdiffusive motion and theta oscillations of neural population activity patterns.” Science Advances 8.16 (2022): eabl4995.

4. Chen, Guozhang, Cheng Kevin Qu, and Pulin Gong. “Anomalous diffusion dynamics of learning in deep neural networks.” Neural Networks 149 (2022): 18-28.

5. Chen, Guozhang, and Pulin Gong. “Computing by modulating spontaneous cortical activity patterns as a mechanism of active visual processing.” Nature communications 10.1 (2019): 4915.