I am currently a Ph.D. student in the Joint Ph.D. Program between Zhejiang University and Westlake University (enrolled in the Fall of 2024). I conduct my research at the School of Engineering, Westlake University, where I am privileged to be supervised by Prof. Yaochu Jin.
My research focuses on Brain-inspired Computing, specifically enhancing the performance of Spiking Neural Networks (SNNs) to tackle increasingly complex tasks. I am passionate about bridging the gap between biological efficiency and artificial intelligence.
I am always open to collaborations or discussions regarding SNNs and neuromorphic computing. Feel free to reach out—let’s connect!
Educations
- 2019.09 - 2023.06, B.E. in Computer Science and Technology (East China University of Science and Technology)
- 2023.09 - 2024.06, M.S. in Computer Science and Technology (East China University of Science and Technology, Withdrawn)
- 2024.09 - 2029.06 (Expected), Ph.D. Student in Computer Science and Technology (School of Computer Science, Zhejiang University).
News
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2026.07: 🎉🎉 One paper on temporal modeling in Spiking Transformers was accepted for publication in Neural Networks!
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2026.07: 🎉🎉 One review paper on attention mechanisms in SNNs was accepted for publication in Journal of Automation and Intelligence!
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2026.05: 🎉🎉 One paper on mitigating visual hallucinations in MLLMs was accepted to ICML 2026!
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2025.06: 🎉🎉 One paper on SNNs for Image Classification was accepted by ICCV-2025!
Publications
Brain-Inspired Computing
Rethinking Attention Locality in Spiking Transformers
Zeqi Zheng, Zizheng Zhu, Yuping Yan, et al.
- Rethinks attention locality in Spiking Transformers, revealing that computational locality does not necessarily translate into spatial locality and that uniform locality enhancement overlooks architectural differences, motivating an architecture-aware locality design.
Enhancing Spiking Transformers with Temporal Feedback Coding and Global-Local Dynamic Neurons
Zeqi Zheng, Zizheng Zhu, Yingchao Yu, et al.
- TFC and GLD-LIF jointly enhance spike pattern diversity and temporal modeling in Spiking Transformers, achieving consistent performance gains with limited computational overhead.
Attention mechanisms in Spiking Neural Networks: From neural encoding to hardware implementation
Doudou Wu*, Zeqi Zheng*, Yaochu Jin†
- This survey systematically reviews attention mechanisms in SNNs, spanning neural encoding, algorithmic design, and neuromorphic hardware implementation, while highlighting key challenges and future directions.
SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition
Zeqi Zheng*, Yancheng Huang*, Yingchao Yu, et al.
- SpiLiFormer incorporates brain-inspired lateral inhibition to mitigate attention distraction in Spiking Transformers, achieving SOTA performance.
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TDFormer: A Top-Down Attention-Controlled Spiking Transformer
Zizheng Zhu*, Yingchao Yu*, Zeqi Zheng*, et al.
- TDFormer introduces top-down attention to Spiking Transformers, enhancing temporal information integration with SOTA performance.
Others
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Spinal-inspired Artificial Tactile Interneuron with High-order Burst Spiking for Intelligent Edge Interfaces
Fanfan Li, Zhanglu Yan, Jiayi Mao, Guolei Liu, Huihui Ren, Bangbang Qin, Zhongfang Zhang, Haiyue Zhang, Yiyang Shen, Zeqi Zheng, Weilong Feng, Dingwei Li, Yingjie Tang, Saisai Wang, Yaochu Jin, Tao Luo, Weng-fai Wong, Hong Wang, Bowen Zhu
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Mitigating Visual Hallucinations via Semantic Curriculum Preference Optimization in MLLMs
Yuanshuai Li, Yuping Yan, Junfeng Tang, Yunxuan Li, Zeqi Zheng, Yaochu Jin
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Sparse Autoencoders Bridge The Deep Learning Model and The Brain
Ziming Mao, Jia Xu, Zeqi Zheng, Haofang Zheng, Dabing Sheng, Yaochu Jin, Guoyuan Yang
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Junfeng Tang, Yuping Yan, Zihan Ye, Zhenshou, Song, Zeqi Zheng, Yaochu Jin
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A Personalized Federated Framework for Document-Level Biomedical Relation Extraction
Yan Xiao, Yaochu Jin, Haoyu Zhang, Xu Huo, Qiqi Liu, Zeqi Zheng
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Federated Graph Neural Networks with Bipartite Embedding for Multi-objective Facility Location
Zeqi Zheng, Ziqi Wang, Xueming Yan, Yaochu Jin, Shiqing Liu, Qiqi Liu
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Multi-medvit: A Deep Learning Approach for the Diagnosis of COVID-19 with the CT Images
Yunjie Cai, Zeqi Zheng, Shanling Nie, Yue Guo, Ruijie Zhang, Hai Yang
Academic Services
- Conference Reviewer: AAAI 2026, ACM-MM 2026, AAAI 2027
- Journal Reviewer: Complex & Intelligent Systems, IEEE Transactions on Cognitive and Developmental Systems
Honors and Awards
- 2023 Best Student Paper Award (DOCS 2023)
- 2019-2023 School Academic Scholarship (First & Second Prize)