我现在是 BrainCog 实验室的助理研究员。我目前主要研究类脑智能、脑启发 LLM、脉冲神经网络、基于事件的视觉等。在此之前，我在中国科学院自动化研究所攻读博士学位，导师是曾毅研究员。我本科毕业于西安电子科技大学数学与统计学院。

类脑智能、脑启发 LLM、脉冲神经网络、基于事件的视觉等

融合神经元精细建模的多神经环路以及学习机制协同的脉冲神经网络研究，国家自然科学基金青年科学基金，2025.01-2027.12

1. Shen Guobin, Zhao Dongcheng, Li Tenglong, Li Jindong, Zeng Yi. Are Conventional SNNs Really Efficient? A Perspective from Network Quantization[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024: 27538-27547. (EI, CCF A)
2. He Xiang, Zhao Dongcheng, Li Yang, Shen Guobin, Kong Qingqun, Zeng Yi. An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain. AAAI, 2024, Oral, Co-First Author (EI, CCF A)
3. Shen Sicheng, Zhao Dongcheng, Shen Guobin, Zeng Yi. TIM: An Efficient Temporal Interaction Module for Spiking Transformer. IJCAI, 2024, Co-First Author. (EI, CCF A)
4. Shen Guobin, Zhao Dongcheng, Dong Yiting, Zeng Yi. Brain-inspired neural circuit evolution for spiking neural networks[J]. Proceedings of the National Academy of Sciences, 2023, 120(39): e2218173120. Co-First Author (SCI)
5. Zhao Dongcheng, Zeng Yi, Li Yang. Backeisnn: A deep spiking neural network with adaptive self-feedback and balanced excitatory–inhibitory neurons[J]. Neural Networks, 2022, 154: 68-77. (SCI) 

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