Published on by China Scientist

Prof. Xiao Wang | Computer Vision | Best Researcher Award 

Xiao Wang is an associate professor at the School of Computer Science and Technology at Anhui University. He earned his bachelor degree from West Anhui University and a doctoral degree in computer science from Anhui University, with additional training as a visiting scholar at Sun Yat-sen University and the University of Sydney. He later conducted postdoctoral research at Pengcheng Laboratory in Shenzhen. His research focuses on computer vision, event-based vision, machine learning, and pattern recognition. He has contributed to advancing multi-modal learning and large-scale pre-trained models while serving as an associate editor and reviewer for leading international journals and conferences.

Prof. Xiao Wang | Anhui University | China

Profiles

ORCID

Education

  • Xiao Wang completed his bachelor studies at West Anhui University in Luan, China. He then pursued a doctoral degree in computer science at Anhui University in Hefei, China, under the guidance of Professors Jin Tang and Bin Luo as part of the Multi-Modal Intelligent Computing Group. During his doctoral studies, he broadened his academic exposure through visiting scholar positions at Sun Yat-sen University under Professor Liang Lin and at the University of Sydney in the UBTECH Sydney Artificial Intelligence Centre under Professor Dacheng Tao.

Experience

  • After his doctoral training, he worked as a postdoctoral researcher at Pengcheng Laboratory in Shenzhen, where he collaborated with Professors Feng Wu, Yonghong Tian, and Yaowei Wang. He currently serves as an associate professor at the School of Computer Science and Technology at Anhui University in Hefei. In addition to his teaching and research duties, he also acts as an associate editor for a leading IEEE journal and participates as a program committee member for top international conferences, while frequently serving as a reviewer for prestigious journals and conferences in computer vision and artificial intelligence.

Awards and Recognition

  • He is a recognized member of IEEE and has been entrusted with influential editorial, reviewing, and committee responsibilities. These roles demonstrate the recognition of his professional standing and the trust placed in him by the global academic community.

Skills and Expertise

  • Xiao Wang has strong expertise in event-based vision, deep learning, visual tracking, artificial intelligence, and representation learning. His skills extend beyond technical knowledge, as evidenced by his active editorial roles, peer-review commitments, and program committee services, reflecting his ability to guide and evaluate cutting-edge research.

Research Focus 

  • His research primarily concentrates on computer vision, event-based vision, machine learning, and pattern recognition. He has developed innovative methods for pedestrian attribute recognition across domains, enhanced by large language model frameworks. He has also contributed surveys and analyses on large-scale multi-modal pre-trained models, offering comprehensive insights into architectures, challenges, and future trends.

Publications

Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey
Authors: Wang, Xiao; Chen, Guangyao; Qian, Guangwu; Gao, Pengcheng; Wei, Xiao-Yong; Wang, Yaowei; Tian, Yonghong; Gao, Wen
Journal: ArXiv

Tiny Object Tracking: A Large-Scale Dataset and a Baseline
Authors: Zhu, Yabin; Li, Chenglong; Liu, Yao; Wang, Xiao; Tang, Jin; Luo, Bin; Huang, Zhixiang
Journal: IEEE Transactions on Neural Networks and Learning Systems

Learning Bottleneck Transformer for Event Image-Voxel Feature Fusion based Classification
Authors: Yuan, Chengguo; Jin, Yu; Wu, Zongzhen; Wei, Fanting; Wang, Yangzirui; Chen, Lan; Wang, Xiao
Journal: ArXiv

Learning CLIP Guided Visual-Text Fusion Transformer for Video-based Pedestrian Attribute Recognition
Authors: Zhu, Jun; Jin, Jiandong; Yang, Zihan; Wu, Xiaohao; Wang, Xiao
Journal: ArXiv

Pedestrian Attribute Recognition: A Survey
Authors: Wang, Xiao; Zheng, Shaofei; Yang, Rui; Zheng, Aihua; Chen, Zhe; Tang, Jin; Luo, Bin
Journal: ArXiv

Conclusion

  • Xiao Wang has steadily progressed from undergraduate studies to postdoctoral research and now holds a respected academic position at Anhui University. His journey highlights a balance of theoretical innovation and practical contributions to computer vision and artificial intelligence. With his leadership in multi-modal learning and strong engagement in the global research community, he continues to make significant impacts in the field.

Xiao Wang | Computer Vision | Best Researcher Award

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