Qianhui Liu Qianhui Liu

Qianhui Liu

I am a Full Professor at Shandong University in Jinan, China. From 2022 to 2025, I was a Research Fellow at the National University of Singapore (NUS), Singapore, working in the Human Language Technology (HLT) Lab with Prof. Haizhou Li. I received my PhD and Bachelor’s degrees from Zhejiang University (ZJU), Hangzhou, China, in 2021 and 2016, respectively, under the supervision of Prof. Gang Pan and Prof. Huajin Tang.

My research interests include spiking neural networks: encoding, learning and architecture design; event-based vision: object/motion/emotion recognition, tracking; (audio-only or audio-visual) speech processing: recognition, keyword spotting and voice activity detection.

🏫 Education

  • 2022.01 - 2025.03, Research Fellow, Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore.
  • 2016.09 - 2021.09, Ph.D., College of Computer Science and Technology, Zhejiang University (ZJU), China.
  • 2012.09 - 2016.06, B.Eng., College of Computer Science and Technology, Zhejiang University (ZJU), China.

📝 Selected Publications

* Co-first author, # Corresponding author

  • Neural Architecture Search of Time-to-First-Spike-Coded Spiking Neural Networks for Efficient Eye-based Emotion Recognition, Qianhui Liu, Jing Yang, Miao Yu, Trevor E. Carlson, Gang Pan, Haizhou Li, Zhumin Chen, ACM International Conference on Multimedia (MM), 2026.
  • ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization, Kaiwen Tang, Di Yu, Jiaqi Zheng, Changze Lv, Qianhui Liu, Zhanglu Yan, Weng-Fai Wong, ACM International Conference on Multimedia (MM), 2026.
  • Lightweight and Personalized Single-Eye Emotion Recognition via CNN-SNN Spatiotemporal Learning and Memory-Inferred Event Features, Qianhui Liu, Jiqing Zhang, Yang Wang, Malu Zhang, Xin Yang, Gang Pan, Haizhou Li, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2026.
  • SpikeTrack: High-performance and Energy-efficient Event-Based Object Tracking with Spiking Neural Network, Yang Wang, Jiqing Zhang, Chuanyu Sun, Qianhui Liu, Huilin Ge, Ziqi Wei, Xin Yang, CVPR, 2026.
  • Otters: An Energy-Efficient SpikingTransformer via Optical Time-to-First-Spike Encoding, Zhanglu Yan, Jiayi Mao, Qianhui Liu, Fanfan Li, Gang Pan, Tao Luo, Bowen Zhu, Weng-Fai Wong, ICLR, 2026.
  • Human-Inspired Computing for Robust and Efficient Audio-Visual Speech Recognition, Qianhui Liu, Jiadong Wang, Yang Wang, Xin Yang, Gang Pan, Haizhou Li, IEEE Transactions on Computers (TC), 2025.
  • Spiking Neural Networks with Adaptive Membrane Time Constant for Event-Based Tracking, Jiqing Zhang, Malu Zhang, Yuanchen Wang, Qianhui Liu#, Baocai Yin, Haizhou Li, Xin Yang, IEEE Transactions on Image Processing (TIP), 2025.
  • Two-Stream Spiking Neural Network for Event-based Action Recognition, Lian Shuang, Qianhui Liu*, Ziling Wang, Jia Su, Zhibin Zuo, Yi Zhang, Rui Yan, Huajin Tang, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025.
  • LitE-SNN: Designing Lightweight Spiking Neural Network through Compressive Network Search and Joint Optimization, Qianhui Liu, Jiaqi Yan, Malu Zhang, Gang Pan, Haizhou Li, The 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.
  • Intelligent Event-Based Lip-Reading Word Classification with SNN Using Spatio-Temporal Attention Features and Triplet Loss, Qianhui Liu, Meng Ge, Haizhou Li, Information Sciences, 2024.
  • Efficient Spiking Neural Network Design via Neural Architecture Search, Jiaqi Yan, Qianhui Liu*, Malu Zhang, Lang Feng, De Ma, Haizhou Li, Gang Pan, Neural Networks, 2024.
  • SVAD: A Robust, Low Power and Real-time Voice Activity Detection Using Spiking Neural Networks, Qu Yang, Qianhui Liu*#, Nan Li, Meng Ge, Zeyang Song, Haizhou Li. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024.
  • ED-sKWS: Early-Decision Spiking Neural Networks for Rapid and Energy-Efficient Keyword Spotting, Zeyang Song, Qianhui Liu#, Qu Yang, Yizhou Peng, Haizhou Li, Interspeech, 2024.
  • Learnable Surrogate Gradient for Direct Training Spiking Neural Networks, Shuang Lian, Jiangrong Shen, Qianhui Liu, Ziming Wang, Rui Yan, Huajin Tang, The 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
  • Adaptive Traffic Signal Control on Devices with Extremely Limited Resources, Dong Xing, Qian Zheng, Qianhui Liu, Gang Pan. The 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.
  • Training Deep Convolutional Spiking Neural Networks with Spike Probabilistic Global Pooling, Shuang Lian, Qianhui Liu, Rui Yan, Huajin Tang, Neural Computation, 2022.
  • Event-based Multimodal Spiking Neural Networks Using Attention Mechanism, Qianhui Liu, Dong Xing, Lang Feng, Huajin Tang, Gang Pan, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.
  • Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks, Lang Feng, Qianhui Liu, Huajin Tang, De Ma, Gang Pan. The 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.
  • Event-based Action Recognition Using Motion Information and Spiking Neural Networks, Qianhui Liu, Dong Xing, Huajin Tang, De Ma, Gang Pan, The 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021.
  • Learning with Generated Teammates to Achieve Type-Free Ad-Hoc Teamwork, Dong Xing, Qianhui Liu, Qian Zheng, Gang Pan, The 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021.
  • Effective AER Object Classification Using Segmented Probability-Maximisation Learning in Spiking Neural Networks, Qianhui Liu, Haibo Ruan, Dong Xing, Huajin Tang, Gang Pan, The 34th AAAI Conference on Artificial Intelligence (AAAI), 2020.
  • Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons, Qianhui Liu, Gang Pan, Haibo Ruan, Dong Xing, Qi Xu, Huajin Tang, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020.

🎖 Awards

  • Runner-up of Intel Neuromorphic Deep Noise Suppression Challenge, Intel.
  • Zhejiang Lab’s International Talent Fund for Young Professionals, Zhejiang Lab.
  • National Scholarship, Ministry of Education.
  • Doctoral Scholarship of Zhejiang University, Zhejiang University.
  • Award of Honor for Graduate, Zhejiang University.
  • Best Academic Paper Award of the 353 Doctoral Innovation Forum, Zhejiang University.