Qianzhu Li named an Academic Star at the 4th Brain Science and Brain-Inspired Intelligence Graduate Forum
Her talk combined the fly connectome with whole-brain modeling to reveal circuit mechanisms of resting-state neural dynamics.
News
2026
Yuxiang Huan and Chaoming Wang organized the CNS2026 symposium “Brain Simulation Frontiers: Models, Software, and Hardware”
Symposium S54 at the 19th National Conference of the Chinese Neuroscience Society, with talks from UESTC, Fudan University, Tsinghua University, Peking University and Pengcheng Laboratory; Chaoming Wang spoke on “Connectome-Driven Differentiable Digital Twin Brain Modeling”.
Wenhao Ping and Qianzhu Li presented at the PhD, Postdoc and Early-Career Faculty Forum of the 8th Chinese Conference on Computational and Cognitive Neuroscience
Talk: “Connectome-constrained whole-brain modeling reveals circuit mechanisms of resting-state dynamics in Drosophila”. The conference was held at the University of Electronic Science and Technology of China, Chengdu.
Digital zebrafish and cognitive computing brain system released at WAIC 2026
ΣBrains-Lab was officially released at the World Artificial Intelligence Conference; see the GDIIST report.
Chaoming Wang spoke at GDIIST's 11th PI “Research Journey” sharing session
His talk, “Feet on the ground, eyes on the stars”, traced his path from computational neuroscience to brain-inspired computing; co-presented with Distinguished Researcher Lan Bao.
“Model-agnostic linear-memory online learning in spiking neural networks” published in Nature Communications
Open-source implementation: BrainTrace.
2025
Chaoming Wang taught lecture 21 of GDIIST's “Research Techniques and Methods” course: hands-on multiscale modeling of biological neural networks
Using the BrainX ecosystem, the lecture walked through building, simulating and training dendritic neuron models, Hodgkin-Huxley-type cells, LIF networks and firing-rate models.
First Brain-Inspired Computing Training Camp held in Hengqin
Co-hosted by GDIIST and the Zhuhai Neuroscience Society from 28 to 31 August; participants built neural network models with BrainPy and ran them on the Tianqin neuromorphic computing platform.
“Integrating physical units into high-performance AI-driven scientific computing” published in Nature Communications
Open-source implementations: BrainUnit and SAIUnit.
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