Kang Wenxiong, Ph.D., Professor of the School of Automation Science and Engineering at South China University of Technology (SCUT), Deputy Director of the Guangdong Provincial Enterprise Key Laboratory on Intelligent Financial; Director of the SCUT-BenLiu AI Joint Laboratory, Head of the SCUT Biometric Recognition and Intelligent Perception Laboratory (BIPLAB); Member of IEEE, ACM, and CCF. He was a visiting researcher and visiting scholar at the Federal Institute of Technology Zurich, Switzerland and the University of Sydney, Australia from 2009.9-2010.6 and 2016.11-2017.12, respectively. His current research interests include image processing, computer vision, pattern recognition, natural language processing, biometric recognition, and deep learning.
In recent years, he has published more than 80 papers in various IEEE journals, including Pattern Recognition, Chinese Science, Journal of Automation and other important professional journals at home and abroad, as well as ICCV, AAAI, ECCV, IJCB, ICPR, ICASSP, and CCBR, including more than 30 papers in SCI journals. Several of his papers have won the Best Paper Award and Outstanding Paper Award. He has applied for 6 international invention patents, authorized 4 international patents, and applied for more than 60 national invention patents and utility model patents. He has authorized more than 40 and has transferred 16 patents to several enterprises, respectively. He has been invited to organize, preside over, and participate in several domestic and international academic conferences in his field, and has served as a member of IEEE T-PAMI, IEEE T-IP, IEEE T-IFS, IEEE T-SMC, IEEE T-HMS, IEEE T-BME, IEEE T-IM, IEEE SPL, ACM T-MCCA, ACM TOMM, Neurocomputing, PR, PRL, Image and Vision Computing, IET Biometrics, IET Image processing, Neural Computing and Applications, Journal of Computer Science, Journal of Automation in English and Chinese, etc. He has also served as the reviewer of important academic journals at home and abroad, as well as the area chair, program committee member, session chair, and reviewer of various prestigious conferences, including ICPR, IJCB, PRCV，ISBA, DICTA, ACMMM, China Control Conference, and China Biometric Recognition Conference.
Biometric recognition, computer vision and pattern recognition, natural language processing, and deep learning.
His current Projects include the National Natural Science Foundation of China (NSFC), Guangdong Provincial Natural Science Foundation, Guangdong Provincial Science and Technology Program, and Enterprise-funded R&D projects. The research covers the following areas:
Ø Research on fast palm vein recognition system
Ø Research on face and gait fusion recognition algorithm
Ø Research on Full-View Three-Dimensional Finger Vein Recognition
Ø Research on Random Hand Gesture Authentication
Ø 3D Hand Pose and Body Pose Estimation
Ø Video understanding and analysis in airport and grid scenarios
 Y. Zhang, X. Wang, M. Shakeel, H. Wan, W. Kang*, Learning Upper Patch Attention using Dual-branch training strategy for Masked Face Recognition, Pattern Recognition, Accept (SCI IF=3.965，JCR Q1)
[2 ] J. Huang, M. Tu, W. Yang and W. Kang*, Joint Attention Network for Finger Vein Authentication. IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-11, 2021.
 Z. Zhang, F. Zhong and W. Kang*, Study on Reflection-Based Imaging Finger Vein Recognition, IEEE Transactions on Information Forensics and Security, doi: 10.1109/TIFS.2021.3093791.
 W. Jia, W. Xia, B. Zhang, Y. Zhao, L. Fei, W. Kang, D. Huang, G. Guo, A survey on dorsal hand vein biometrics, Pattern Recognition 120, 108122 (SCI IF=3.965，JCR Q1)
 H. Xu, W. Yang, Q. Wu, W. Kang*, Endowing Rotation Invariance for 3D Finger Shape and Vein Verification，Frontiers of Computer Science, Accept (SCI )
J.Xu, H. Tian , Z. Wang, Y. Wang, W. Kang, F.Chen,Joint Input and Output Space Learning for Multi-Label Image Classification. IEEE Transactions on Multimedia. 23: 1696-1707 (2021) (SCI IF=3.977，JCR Q1)
 C. Liu , Y. Yang, X. Liu, L. Fang, and W. Kang*, Dynamic Hand Gesture Authentication Dataset and Benchmark, IEEE Transactions on Information Forensics and Security, 2021(16): 1550-1562. (SCI IF=5.824，JCR Q1)
 H. Xu, L. Wang, Q. Wu, W. Kang*. PVLNet: Parameterized-View-Learning neural network for 3D shape recognition. Computers & Graphics. 98: 71-81 (2021)
 W. Yang, W. Luo, W. Kang*, Z. Huang and Q. Wu, FVRAS-Net: An Embedded Finger-Vein Recognition and AntiSpoofing System Using a Unified CNN. IEEE Transactions on Instrumentation & Measurement, 2020(69)11: 8690-8701. (SCIIF=3.84. JCR Q1)
 G. Chen, G. Pan, Y. Zhou, W. Kang*, J. Hou, F. Deng, Correlation Filter Tracking via Distractor-aware Learning and Multi-Anchor Detection, IEEE Transactions on Circuits and Systems for Video Technology,2020(30)12: 4810-4822 (SCI IF=4.133，JCR Q1)
 W. Kang*, H. Liu, W. Luo, F. Deng, Study of a Full-View 3D Finger Vein Verification Technique, IEEE Transactions on Information Forensics and Security, (2020)15(1): 1175-1189 (SCI IF=5.824，JCR Q1)
 L. Fang, N. Liang, W. Kang*, Z. Wang, D. Feng, Real-time hand posture recognition using hand geometric features and Fisher Vector, Signal Processing: Image Communication, 2020.(82):115729, (SCI IF=2.779. JCR Q2)
 W. Kang*, Yuting Lu, Dejian Li, Wei Jia, From Noise to Feature: Exploiting Intensity Distribution as a Novel Soft Biometric Trait for Finger Vein Recognition, IEEE Transactions on Information Forensics & Security, (2019)14(4): 858-869. (SCI IF=5.824，JCR Q1)
 A.Deng, S.Wang, W.Kang, F.Deng, On the Importance of Different Frequency Bin for Speaker Verification, ICASSP 2022, Accept
 H.Xu, Z.Zhou, Y.Wang, W.Kang, B. Sun, H.Li, Y. Qiao, Digging into Uncertainty in Self-supervised Multi-view Stereo, ICCV 2021, Accept
 W.Song, W.Kang*, Y.Yang, L.Fang, C.Liu, X,Liu, TDS-Net: Towards Fast Dynamic Random Hand Gesture Authentication via Temporal Difference Symbiotic Neural Network，IJCB 2021, Accept as Best paper
 W.Yang, Z.Chen, J.Huang, L.Wang, W.Kang*, LFMB-3DFB: A Large-scale Finger Multi-Biometric Database and Benchmark for 3D Finger Biometrics，IJCB 2021, Accept as Best paper
 C.Luo, W.Kang*, J.Zhao, X.Guo, A.Deng, W.Xu, Learning Discriminative Speaker Embedding by Improving Aggregation Strategy and Loss Function for Speaker Verification，IJCB 2021, Accept as short oral
 H.Xu, Z.Zhou, Y.Qiao, W.Kang, Q.Wu, Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation，AAAI 2021, Accept as Distinguished paper
 L.Fang, X.Liu, L.Liu, H.Xu, W. Kang*，JGR-P2O: Joint Graph Reasoning based Pixel-to-Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Image，ECCV 2020，Accept as spotlight (top 5% of submissions)
 Z.Su, L.Fang, W. Kang, D.Hu, M. Pietikäinen, L.Liu，Dynamic Group Convolution for Accelerating Convolutional Neural Networks，ECCV 2020，Accept as spotlight (top 5% of submissions)
 N. Liang, W. Xu, C. Luo and W. Kang*, Learning the Front-end Speech Feature with Raw Waveform for End-to-end Speaker Recognition. ICCAI 2020,Accept
 H. Xu, L. Fang, X. Liang*, W. Kang, Z. Li, Universal-RCNN: Universal Object Detector via Transferable Graph R-CNN, AAAI 2020, Oral. Accept