Personal Profile
Wu Si, Professor at South China University of Technology, Member of the Chinese Association for Artificial Intelligence, and Member of the Technical Committee on Machine Learning. Main research areas include artificial intelligence, machine learning, and computer vision. Has published over 60 papers in international journals and conferences such as IEEE Transactions on Image Processing (TIP), IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Multimedia (TMM), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV), Association for the Advancement of Artificial Intelligence (AAAI), and International Joint Conference on Artificial Intelligence (IJCAI). Among these publications, more than 30 are journal papers in the IEEE Transactions series or classified as CCF-A ranked venues. Awarded the Second Prize of Guangdong Scientific and Technological Progress Award in 2019. Led multiple projects funded by national and provincial natural science foundations, and participated in national major science and technology special programs and the Guangdong Provincial Key Research and Development Program.
Education Background
2009-2012, City University of Hong Kong, Doctor of Philosophy
2006-2008, Huazhong University of Science and Technology, Master of Science
2002-2006, Huazhong University of Science and Technology, Bachelor of Science
Work Experience
2014-Present, South China University of Technology, Associate Professor, Professor
2013-2014, School of Electrical Engineering and Computer Science, University of Ottawa, Canada, Postdoctoral Researcher
Research Projects
[1] General Program of the National Natural Science Foundation of China, Research on Key Technologies for Human Detection under Limited Annotation Conditions (62072189)
[2] General Program of the Guangdong Provincial Natural Science Foundation, Research on Pedestrian Detection in Surveillance Videos under Semi-supervised Conditions (2020A1515010484)
Flagship Achievements
[1] Y. Liu, X. Huo, T. Chen, X. Zeng, S. Wu*, Z. Yu, and H. Wong, “Mask-embedded discriminator with region-based semantic regularization for semi-supervised class-conditional image synthesis,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[2] G. Li, Q. Jiao, S. Qian, S. Wu*, and H. Wong, “High fidelity GAN inversion via prior multi-subspace feature composition,” in AAAI Conference on Artificial Intelligence (AAAI), 2021.
[3] J. Li, S. Wu*, C. Liu, Z. Yu and H. Wong, “Semi-supervised deep coupled ensemble learning with classification landmark exploration,” IEEE Transactions on Image Processing, vol. 29, pp. 538-550, 2020.
[4] S. Wu, S. Lin, W. Wu, M. Azzam, and H. Wong, “Semi-supervised pedestrian instance synthesis and detection with mutual reinforcement,” in IEEE/CVF International Conference on Computer Vision (ICCV), 2019.
[5] S. Wu, J. Zhong, W. Cao, R. Li, Z. Yu, and H. Wong, “Improving domain-specific classification by collaborative learning with adaptation networks,” in AAAI Conference on Artificial Intelligence (AAAI), 2019.
