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Yan Zhanglu 严章路

Research Fellow
National University of Singapore
zlyan@nus.edu.sg


About Me

I am a Research Fellow at National University of Singapore (NUS). I received the BSc degree in Computer Science from Xi’an Jiaotong University in 2019, the MSc degree in Artificial Intelligence from the NUS in 2020, and the PhD degree in Computer Science from NUS in 2024. My CV is attached:)

Research Interests

Investigating the inner mechanisms of spiking neural networks across material, circuit, architecture, algorithm, and application levels, with the goal of developing truly energy-efficient SNN systems.

News

Publications

  1. NC
    Spinal-inspired artificial tactile interneuron with high-order burst spiking for intelligent edge interfaces
    Fanfan Li#, Zhanglu Yan#, J. Mao, G. Liu, H. Ren, B. Qin, Z. Zhang, H. Zhang, Y. Shen, Z. Zheng, W. Feng, D. Li, Y. Tang, S. Wang, Y. Jin, T. Luo, W.-f. Wong, Hong Wang, Bowen Zhu (#Equal contributions)
    Nature Communication (NC), 2026.

  2. TCAD
    SparrowSNN: A hardware/software co-design for energy efficient ECG classification
    Zhenyu Bai, Zhanglu Yan*, Gao Bin, Tulika Mitra, Weng-Fai Wong (*Corresponding authors)
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2026.

  3. ICLR
    Otters: An Energy-Efficient Spiking Transformer via Optical Time-to-First-Spike Encoding
    Zhanglu Yan*, Jiayi Mao, Qianhui Liu, Fanfan Li, Tao Luo, Gang Pan, Bowen Zhu, Weng-Fai Wong (*Corresponding authors)
    The Fourteenth International Conference on Learning Representations (ICLR), 2026.

  4. ACC
    HyperSNN: A new efficient and robust deep learning model for resource constrained control applications
    Zhanglu Yan, Shida Wang, Kaiwen Tang, Zhenyu Bai, Weng-Fai Wong
    The American Control Conference (ACC), 2026.
    Oral presentation

  5. WWW
    Energy-Efficient and Dequantization-Free Q-LLMs: A Spiking Neural Network Approach to Salient Value Mitigation
    Chenyu Wang, Zhanglu Yan*, Zhi Zhou*, Xu Chen, Weng-Fai Wong (*Corresponding authors)
    THE ACM WEB CONFERENCE 2026 (WWW), 2026.

  6. ASPLOS
    A Data-Driven Dynamic Execution Orchestration Architecture
    Zhenyu Bai, Pranav Dangi, Rohan Juneja, Zhaoying Li, Zhanglu Yan, Huiying Lan, Tulika Mitra
    The 2026 International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2026.

  7. ICML
    Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
    Kaiwen Tang, Zhanglu Yan*, Weng-Fai Wong (*Corresponding authors)
    International Conference on Machine Learning (ICML), 2025.
    PDF Code

  8. TNNLS
    Low Latency Conversion of Artificial Neural Network Models to Rate-encoded Spiking Neural Networks
    Zhanglu Yan, Kaiwen Tang, Jun Zhou, Weng-Fai Wong
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025.
    PDF Code

  9. IJCNN
    OneSpike: Ultra-low latency spiking neural networks
    Kaiwen Tang#, Zhanglu Yan#*, Weng-Fai Wong (*Corresponding authors,#Equal contributions)
    International Joint Conference on Neural Networks (IJCNN), 2024.
    Code

  10. ACS Synth. Biol
    Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences
    Zhanglu Yan#*, Weiran Chu#, Yuhua Sheng, Kaiwen Tang, Shida Wang, Yanfeng Liu*, Weng-Fai Wong (*Corresponding authors,#Equal contributions)
    ACS Synthetic Biology (ACS Synth. Biol), 2024.
    PDF

  11. CEJ
    Numerical solution-based algorithm assisted development of a continuous flow microwave reactor
    Huayu Yang, Zhanglu Yan, Huacheng Zhu, Bowen Yan, Wei Chen, Daming Fan
    Chemical Engineering Journal (CEJ), 2024.

  12. TPAMI
    CQ + Training: Minimizing Accuracy Loss in Conversion from Convolutional Neural Networks to Spiking Neural Networks
    Zhanglu Yan*#, Jun Zhou#, Weng-Fai Wong (*Corresponding authors,#Equal contributions)
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
    PDF Code

  13. ECML
    Efficient Hyperdimensional Computing
    Zhanglu Yan, Shida Wang, Kaiwen Tang, Weng-Fai Wong
    Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML), 2023.
    PDF Code Oral presentation

  14. SH
    EEG classification with spiking neural network: Smaller, better, more energy efficient
    Zhanglu Yan, Jun Zhou, Weng-Fai Wong
    Smart Health (SH), 2022.

  15. AAAI
    Near lossless transfer learning for spiking neural networks
    Zhanglu Yan*#, Jun Zhou#, Weng-Fai Wong (*Corresponding authors,#Equal contributions)
    Proceedings of the AAAI conference on artificial intelligence (AAAI), 2021.
    PDF Code

  16. BSPC
    Energy efficient ECG classification with spiking neural network
    Zhanglu Yan, Jun Zhou, Weng-Fai Wong
    Biomedical Signal Processing and Control (BSPC), 2021.

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