I received my Ph.D. from Xi’an Jiaotong University in December 2023, under the supervision of Professor Guangshe Zhao.

I am currently an Assistant Professor at the Brain-inspired Computing Laboratory, Institute of Automation, Chinese Academy of Sciences, led by Professor Guoqi Li.

My research interests include brain-inspired computing, neuromorphic computing, spiking neural networks, foundation models, and dynamic computing.

I am seeking highly motivated Interns! Please contact me if you are interested in my research!

📝 Representative Publications

• Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip, Man Yao, Ole Richter, Guangshe Zhao, Ning Qiao, Yannan Xing, Dingheng Wang, Tianxiang Hu, Wei Fang, Tugba Demirci, Michele De Marchi, Lei Deng, Tianyi Yan, Carsten Nielsen, Sadique Sheik, Chenxi Wu, Yonghong Tian, Bo Xu, Guoqi Li, Nature Communications 2024 (ESI Highly Cited Papar).
• Attention spiking neural networks, Man Yao, Guangshe Zhao, Hengyu Zhang, Yifan Hu, Lei Deng, Yonghong Tian, Bo Xu, Guoqi Li, IEEE TPAMI 2023 (ESI Highly Cited Papar).
• Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training, Man Yao, Xuerui Qiu, Tianxiang Hu, Jiakui Hu, Yuhong Chou, Keyu Tian, Jianxing Liao, Luziwei Leng, Bo Xu, Guoqi Li, IEEE TPAMI 2025.
• Spike-driven Transformer, Man Yao, Jiakui Hu, Zhaokun Zhou, Li Yuan, Yonghong Tian, Bo Xu, Guoqi Li, NeurIPS 2023.
• Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips, Man Yao, Jiakui Hu, Tianxiang Hu, Yifan Xu, Zhaokun Zhou, Yonghong Tian, Bo Xu, Guoqi Li, ICLR 2024.
• Temporal-wise attention spiking neural networks for event streams classification, Man Yao, Huanhuan Gao, Guangshe Zhao, Dingheng Wang, Yihan Lin, Zhaoxu Yang, Guoqi Li, ICCV 2021.
• Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection, Xinhao Luo*, Man Yao*, Yuhong Chou, Bo Xu, Guoqi Li, ECCV 2024 (Best Paper Candidate, Acceptance Rate: 0.1%).
• High-Performance Temporal Reversible Spiking Neural Networks with O(L) Training Memory and O(1) Inference Cost, Jiakui Hu*, Man Yao*, Xuerui Qiu, Yuhong Chou, Yuxuan Cai, Ning Qiao, Yonghong Tian, Bo Xu, Guoqi Li, ICML 2024 (Spotlight, Acceptance Rate: 2%).
• MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map, Yuhong Chou*, Man Yao*, Kexin Wang, Yuqi Pan, Ruijie Zhu, Yiran Zhong, Yu Qiao, Jibin Wu, Bo Xu, Guoqi Li, NeurIPS 2024 (Oral, Acceptance Rate: 2%).
• Spike2Former: Efficient Spiking Transformer for High-performance Image Segmentation, Zhenxin Lei, Man Yao#, Jiakui Hu, Xinhao Luo, Yanye Lu, Bo Xu, Guoqi Li#, AAAI 2025 (Oral, Acceptance Rate: 4.6%).