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Yan Zhanglu

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

I’m interested in energy-efficient neuromorphic computing. Previously, I focused on software-level spiking neural networks and biomedical applications. Now, my research has shifted towards neuromorphic architecture, exploring software algorithms from a hardware perspective and pursuing ‘AI + X,’ where X represents hardware applications.

News

Publications

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

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

  9. 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

  10. 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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