Zeqi Zheng

Zeqi Zheng

郑泽麒

Zhejiang University

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  • 2023.09 - 2024.06, M.S. in Computer Science and Technology (East China University of Science and Technology, Withdrawn)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

  • 2025.06:  🎉🎉 One paper on SNNs for Image Classification was accepted by ICCV-2025!

Publications

Brain-Inspired Computing

Arxiv(2508.00387)
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STF: Shallow-Level Temporal Feedback to Enhance Spiking Transformers
Zeqi Zheng*, Zizheng Zhu*, Yingchao Yu, et al.

  • STF introduces shallow-level temporal feedback into spiking Transformers, significantly enhancing spike pattern diversity and performance with minimal computational overhead.
ICCV-2025 (Poster)
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SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition
ZeqiZheng*, 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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Arxiv(2505.15840)
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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

  • Mitigating Visual Hallucinations via Semantic Curriculum Preference Optimization in MLLMs
    Yuanshuai Li, Yuping Yan, Junfeng Tang, Yunxuan Li, Zeqi Zheng, Yaochu Jin

  • Sparse Autoencoders Bridge The Deep Learning Model and The Brain
    Ziming Mao, Jia Xu, Zeqi Zheng, Haofang Zheng, Dabing Sheng, Yaochu Jin, Guoyuan Yang

  • Think Small, Plan Smart: Minimalist Symbolic Abstraction and Heuristic Subspace Search for LLM-Guided Task Planning
    Junfeng Tang, Yuping Yan, Zihan Ye, Zhenshou, Song, Zeqi Zheng, Yaochu Jin

  • A Personalized Federated Framework for Document-Level Biomedical Relation Extraction
    Yan Xiao, Yaochu Jin, Haoyu Zhang, Xu Huo, Qiqi Liu, Zeqi Zheng

  • Federated Graph Neural Networks with Bipartite Embedding for Multi-objective Facility Location
    Zeqi Zheng, Ziqi Wang, Xueming Yan, Yaochu Jin, Shiqing Liu, Qiqi Liu

  • 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

Honors and Awards

  • 2023 Best Student Paper Award (DOCS 2023)
  • 2019-2023 School Academic Scholarship (First & Second Prize)

Welcome