Fushuo Huo (霍赋硕) School of Cyber Science and Engineering Southeast University Location: 424 Library Jiulonghu Campus, Nanjing, China. Research Interest | Education | Publications | Awards Email: fushuohuo AT seu dot edu dot cn;      Phone: +86 18751795276 [Google Scholar] [Github] [Wechat]

Research Interest

• Multimodal Learning; Vision-language Model
• Trustworthy AI; Elastic AI

Education & Experience

• 2025.10-2026.02
  Postdoctoral Fellow. , supervised by Prof. Song Guo and Wenchao Xu, Hong Kong University of Science and Technology.     
• 2022.09-2025.09
  Ph.D. , supervised by Prof. Song Guo and Wenchao Xu, Hong Kong Polytechnic University.     
• 2024.10-2025.09
  Visiting Ph.D. , supervised by Prof. Dacheng Tao, Nanyang Technological University.     
• 2019.09-2022.06
  M.S. , supervised by Prof. Xuegui Zhu and Prof. Lei Zhang, Chongqing University.        
• 2015.09-2019.06
  B.S. , (Minor in Finance) China University of Mining and Technology.         
• 2024.04-2024.11
  Research Intern , supervised by Dr. Zhong Zhang and Dr. Peilin Zhao, Tencent AI Lab.     

Selected Publications

● Q. Nguyen, S. Liang, Y. Li, F. Huo*, D. Tao, “ TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting,” Forty-third International Conference on Machine Learning (ICML) , 2026. [Paper]

● Y. Cui, P. Qi, F. Huo*, H. Du, W. Shi, J. Dai, Z. Zhu, S. Han, Y. Guo, “ Perception, Understanding and Reasoning, A Multimodal Benchmark for Video Fake News Detection,” Annual Meeting of the Association for Computational Linguistics (ACL) main track, 2026. [Paper]

● F. Huo, W. Xu, Z. Zhang, H. Wang, Z. Chen, P. Zhao, “Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models,” International Conference on Learning Representations (ICLR), 2025. [Paper]

● Y. Fan, W. Xu, H. Wang, F. Huo, J. Chen, and S. Guo, “Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection,” European Conference on Computer Vision (ECCV), 2024. [Paper]

● F. Huo, W. Xu, J. Guo, H. Wang, and S. Guo, “C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, Highlight. [Paper]

● F. Huo, W. Xu, S. Guo, J. Guo, H. Wang, and Z. Liu, “PROCC: Progressive cross-primitive consistency for open-world compositional zero-shot learning,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024. [Paper]

● F. Huo, W. Xu, J. Guo, H. Wang, Y. Fan, and S. Guo, “Non-Exemplar Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024. [Paper]

● B. Li, F. Huo* (Corresponding Author), “REQA: Coarse-to-fine Assessment of Image Quality to Alleviate the Range Effect,” Journal of Visual Communication and Image Representation, 2024. [Paper]

● F. Huo, Z. Liu, J. Guo, W. Xu, and S. Guo, “UTDNet: A unified triplet decoder network for multimodal salient object detection,” Neural Networks, 2023. [Paper]

● J. Guo, S. Guo, Q. Zhou, Z. Liu, X. Lu, and F. Huo, “Graph knows unknowns: Reformulate zero-shot learning as sample-level graph recognition,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023. [Paper]

● Z. Liu, S. Guo, X. Lu, J. Guo, J. Zhang, Y. Zeng, and F. Huo, “(ML)$^2$P-Encoder: On Exploration of Channel-Class Correlation for Multi-Label Zero-Shot Learning,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper]

● Z. Liu, S. Guo, J. Guo, Y. Xu, and F. Huo, “Towards Unbiased Multi-Label Zero-Shot Learning with Pyramid and Semantic Attention,” IEEE Transactions on Multimedia, 2022. [Paper]

● F. Huo, X Zhu, and B Li, “Three-stream interaction decoder network for RGB-thermal salient object detection,” Knowledge-Based Systems, 2022. [Paper]

● X. Zhu, Y. Shu, Q. Zhang, and F. Huo, “Spatiotemporal regularization correlation filter with response feedback,” Journal of Electronic Imaging, 2022. [Paper]

● F. Huo, X. Zhu, Q. Zhang, Z. Liu, and W. Yu, “Real-time One-stream Semantic-guided Refinement Network for RGB-Thermal Salient Object Detection,” IEEE Transactions on Instrumentation and Measurement, 2022. [Paper]

● F. Huo, X. Zhu, L. Zhang, Q. Liu, and Y. Shu, “Efficient Context-Guided Stacked Refinement Network for RGB-T Salient Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology, 2022. [Paper]

● F. Huo, B. Li, X. Zhu, “Efficient Wavelet Boost Learning-Based Multi-stage Progressive Refinement Network for Underwater Image Enhancement,” International Conference on Computer Vision Workshop (ICCVW) in Advances in Image Manipulation, [Paper]

● F. Huo, X. Zhu, H. Zeng, Q. Liu, and J. Qiu, “Fast Fusion-Based Dehazing With Histogram Modification and Improved Atmospheric Illumination Prior,” IEEE Sensors Journal, 2021. [Paper]

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Awards

• 2022, Excellent Master Thesis, School of Electrical Engineering.
• 2021, National Scholarship of China, Ministry of Education.
• 2019, The First-class Academic Scholarship, Chongqing University.
• 2017, Second Prize of Jiangsu Mathematics Competition.
• 2016, National Encouragement Scholarship, Ministry of Education.