Dr. Liang Wang received both the B. Eng. and M. Eng. degrees from Anhui University in 1997 and 2000 respectively, and the PhD degree from the Institute of Automation, Chinese Academy of Sciences (CAS) in 2004. From 2004 to 2010, he worked as a Research Assistant at Imperial College London, United Kingdom and Monash University, Australia, a Research Fellow at the University of Melbourne, Australia, and a lecturer at the University of Bath, United Kingdom, respectively.?Currently, he is a full Professor at the National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P. R. China.
His major research interests include machine learning, pattern recognition and computer vision.?He has widely published at highly-ranked international journals such as IEEE TPAMI and IEEE TIP, and leading international conferences such as CVPR, ICCV and AAAI. He has obtained several honors and awards such as the Special Prize of the Presidential Scholarship of Chinese Academy of Sciences. He is a Fellow of IEEE, IAPR, CAAI and CIE, as well as a member of BMVA and ACM. He is currently an associate editor of IEEE TPAMI and IEEE TIP.

Machine learning, pattern recognition, data mining and computer vision

The second prize of the science and technology progress award of China Society of Image and Graphics: Yongzhen Huang, Tieniu Tan, Liang Wang, Chunshui Cao, Jinfeng Yang and Xuemei Jiang, 2021
CAAI Fellow, 2021
IEEE Fellow, 2019
CIE Fellow, 2019
Wider Face and Person Challenge 2019, 1st of Person Search by Language: Kai Niu, Yan Huang, Da Li, Liang Wang
The “winning tracker” award at the Visual Object Tracking RGBD challenge (VOT2019- RGBD): H. Yu, H. Peng, Z. Wu, Y. Huang, J. Fu, L. Wang
Capital Science and Technology Innovation Leading Talents Training Project, 2018
Promotion Plan for Young and Middle-aged Leaders of Science and Technology Innovation, 2017
The fourteen China Youth Science and Technology Award, 2016
National Science Fund for Distinguished Young Scholars, 2015
IAPR Fellow, 2014
National Hundred Excellent Doctoral Thesis Nomination, 2006
Outstanding Doctoral Thesis of Chinese Academy of Sciences, 2005
Beijing Science and Technology Award, the first prize, 2004
CAS President scholarship Excellence Award, 2003

CAAI Fellow，2021-
Vice President of CSIG, 2020-
IEEE Fellow, 2019-
CIE Fellow, 2019-
Associate editor, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2018-
Associate editor, IEEE Trans. on Image Processing (TIP), 2018-
Director of CSIG Big Visual Data Technical Committee, 2017-
Secretary General of the Big Image and Video Data Alliance (BIDA), 2014-
IAPR Fellow, 2014-

Selected books
L. Wang, G. Y. Zhao, L. Cheng, and M. Pietiaainen, Machine learning for vision-based motion analysis: theory and technologies, Springer, ISBN: 978-0-85729-056-4, 372 pages, December 2010.
D. Schonfeld, C. F. Shan, D. C. Tao, and L. Wang, Video search and mining, Springer, ISBN: 978-3-642-12899-8, 386 pages, March 2010.
L. Wang, L. Cheng and G. Y. Zhao, Machine learning for human motion analysis: theory and practice, IGI Global USA, ISBN: 978-1-60566-900-7, 387 pages, December, 2009.
L. Wang and X. Geng, Behavioural biometrics for human identification: intelligent applications, IGI Global USA, ISBN: 978-1-60566-725-6, 488 pages, August 2009.

Selected journal articles
Yan Huang, Jingdong Wang, and Liang Wang, Few-Shot Image and Sentence Matching via Aligned Cross-Modal Memory, IEEE Transactions on Pattern Analysis and Machine Intelligence,44(6):2968-2983, 2021.
Yan Huang, Qi Wu, Wei Wang, and Liang Wang, Image and sentence matching via semantic concepts and order learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(3): 636-650, 2020.
C. S. Cao, Y. Z. Huang, Y. Yang, L. Wang, Z. L. Wang, T. N. Tan,Feedback convolutional neural network for visual localization and segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence,2019, 41(7):1627-1640.
Y. Q. Zhang, Y. Z. Huang, L. Wang, S. Q. Yu, A comprehensive study on gait biometrics via a joint CNN-based method, Patten Recognition, 2019,93:228-236.
L.J. Huang, Y. Huang, W.L. Ouyang, L. Wang, Part-Aligned Pose-Guided Recurrent Network for Action Recognition, Pattern Recognition, 2019,92: 165-176.
Yan Huang, Wei Wang, Liang Wang, Video super-resolution via bidirectional recurrent convolutional networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(4):1015-1028, 2018.
L. Wang, L. Cheng and L. Wang, Elastic sequence correlation for human action analysis, IEEE Transactions on Image Processing (TIP), 2011, 20(6): 1725-1738.
X. Geng, K. Smith-Miles, Z. H. Zhou, and L. Wang, Face image modelling by multilinear subspace analysis with missing values, IEEE Transactions on System, Man, and Cybernetics, Part B (TSMC-B), 2011, 41(3): 881-892.
Y. Song, X. Bai, P. Hall and L. Wang, In search of perceptually salient groupings, IEEE Transactions on Image Processing (TIP), 2011, 20(4): 935-947.
B. Tan, J. P. Zhang and L. Wang, Semi-supervised elastic net for pedestrian counting, Pattern Recognition (PR), 2011, 44(10-11):2297-2304.
L. Wang, C. Leckie, R. Kotagiri, and J. Bezdek, Approximate pairwise clustering for large datasets via sampling plus extension, Pattern Recognition (PR), 2011, 44(2): 222-235.
L. Wang, G. Y. Zhao, N. Rajpoot, and M. Nixon, Special issue on new advances in video-based gait analysis and applications: challenges and solutions, IEEE Transactions on System, Man and Cybernetics – Part B (TSMC-B), 2010, 40(4): 982-985. 
X. Geng, K. Smith-Miles, L. Wang, M. Li, and Q. Wu, Context-aware multi-biometric fusion with application to human identification in video, Pattern Recognition (PR), 2010, 43 (10): 3660-3673. 
L. Wang, X. Geng, J. Bezdek, C. Leckie, and R. Kotagiri, Enhanced visual analysis for cluster tendency assessment and data partitioning, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2010, 22(10): 1401-1414.
H. Zhou, L. Wang and D. Suter, Human action recognition using feature-reduced Gaussian process classification, Pattern Recognition Letters (PRL), 2009, 30(12): 1059-1066.
L. Wang, C. Leckie, R. Kotagiri, and J. Bezdek, Automatically determining the number of clusters in unlabeled data sets, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2009, 21(3): 335-350.
L. Wang and D. Suter, Visual learning and recognition of sequential data manifolds with applications to human movement analysis, Computer Vision and Image Understanding (CVIU), 2008, 110(2): 153-172.
L. Wang, J. C. Bezdek, C. Leckie, and R. Kotagiri, Selective sampling for approximate clustering of very large data sets, International Journal of Intelligence Systems (IJIS), 2008, 23(3): 313-331.
L. Wang and D. Suter, Learning and matching of dynamic shape manifolds for human action recognition, IEEE Transactions on Image Processing (TIP), 2007, 16(6): 1646-1661.
L. Wang, T. N. Tan, H. Z. Ning, and W. M. Hu, Fusion of static and dynamic body biometrics for gait recognition, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2004, 14(2): 149-158.
W. M. Hu, T. N. Tan, L. Wang, and S. Maybank, A survey of visual surveillance of object motion and behaviors, IEEE Transactions on Systems, Man, and Cybernetics - Part C (TSMC-C), 2004, 34(3): 334-352.
H. Z. Ning, T. N. Tan, L. Wang, and W. M. Hu, Kinematics-based tracking of human walking in monocular video sequences, Image and Vision Computing (IVC), 2004, 22: 429-441.
H. Z. Ning, T. N. Tan, L. Wang, and W. M. Hu, People tracking based on motion model and motion constraints with automatic initialization, Pattern Recognition (PR), 2004, 37: 1423-1440.
L. Wang, T. N. Tan, H. Z. Ning, and W. M. Hu, Silhouette analysis based gait recognition for human identification, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2003, 25(12): 1505-1518.
L. Wang, T. N. Tan, W. M. Hu, and H. Z. Ning, Automatic gait recognition based on statistical shape analysis, IEEE Transactions on Image Processing (TIP), 2003, 12(9): 1120-1131.
L. Wang, W. M. Hu and T. N. Tan, Recent developments in human motion analysis, Pattern Recognition (PR), 2003, 36(3): 585-601.

Selected conference articles
Zhengxiong Luo, Zhicheng Wang, Yan Huang, Shang Li, Liang Wang, Tieniu Tan, and Erjin Zhou, “Rethinking the Heatmap Regression for Bottom-Up Human Pose Estimation,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 13264-13273, June 2021, Nashville, United States.
Ya Jing, Tao Kong, Wei Wang, Liang Wang, Lei Li, Tieniu Tan, “Locate then Segment: A Strong Pipeline for Referring Image Segmentation,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 9858-9867, June 2020, Nashville, United States.
Zerui Chen, Yan Huang, Hongyuan Yu, Bin Xue, Ke Han, Yiru Guo, Liang Wang, “Towards Part-Aware Monocular 3D Human Pose Estimation: An Architecture Search Approach,” Proc. European Conference on Computer Vision, pp. 715-732, August 2020, Glasgow, UK.
Ke Han, Yan Huang, Zerui Chen, Liang Wang, Tieniu Tan, “Prediction and Recovery for Adaptive Low-Resolution Person Re-Identification,” Proc. European Conference on Computer Vision, pp. 193 20209, August 2020, Glasgow, UK.
Linjiang Huang, Yan Huang, Wanli Ouyang and Liang Wang, “Part-Level Graph Convolutional Network for Skeleton-Based Action Recognition,” Proc. AAAI Conference on Artificial Intelligence, pp. 11045-11052, February 2020, New York, USA.
Chunfeng Song, Yan Huang, Wanli Ouyang and Liang Wang, “Box-Driven Class-Wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 3136-3145, June 2019, Long Beach, CA, USA.
Chenyang Si, Wentao Chen, Wei Wang, Liang Wang and Tieniu Tan, “An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 1227-1236, June 2019, Long Beach, CA, USA.
Yan Huang, Qi Wu, Chunfeng Song and Liang Wang, “Learning Semantic Concepts and Order for Image and Sentence Matching,” Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp. 6163-6171, June 2018, Salt Lake City, USA.
Chunfeng Song, Yan Huang, Wanli Ouyang and Liang Wang, “Mask-guided Contrastive Attention Model for Person Re-Identification,” Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1179-1188, June 2018, Salt Lake City, USA.
Chenyang Si, Ya Jing, Wei Wang, Liang Wang and Tieniu Tan, “Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning,” Proc. Springer European Conference on Computer Vison, pp. 106-121, September 2018, Munich, Germany.
Chenglong Li, Chengli Zhu, Yan Huang, Jin Tang and Liang Wang, “Cross-Modal Ranking with Soft Consistency and Noisy Labels for Robust RGB-T Tracking,” Proc. Springer European Conference on Computer Vision, pp.831-847, September 2018, Munich, Germany.
C. Wang, J. P. Zhang, J. Pu, X. R. Yuan, and L. Wang, Chrono-gait image: A novel temporal template for gait recognition, Proceedings of European Conference on Computer Vision (ECCV, Poster, 27% acceptance rate), pp. 257-270, 2010.
L. Wang, C. Leckie and R. Kotagiri, Combining real and virtual graphs to enhance data clustering, Proceedings of International Conference on Pattern Recognition (ICPR, Oral), pp. 790-793, 2010.
L. Wang and C. Leckie, Encoding actions via the quantized vocabulary of averaged silhouettes, Proceedings of International Conference on Pattern Recognition (ICPR, Poster), pp. 3657-3660, 2010.
L. Wang, U. Nguyen, C. Leckie, J. Bezdek, and R. Kotagiri, iVAT and aVAT: visual analysis for cluster tendency assessment, Proceedings of 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD, Long, 10.2% acceptance rate), LNAI 6118, pp. 16-27, 2010.
L. Wang, H. Zhou, S. Low, and C. Leckie, Action recognition via multi-feature fusion and Gaussian process classification, Proceedings of International Workshop on Applications of Computer Vision (WACV), pp. 1-6, 2009.
X. Geng, K. Smith-Miles, L. Wang, and Z. H. Zhou, Face image modelling by multilinear subspace analysis with missing values, Proceedings of ACM International Conference on Multimedia (MM), pp. 629-632, 2009.
L. Wang, C. Leckie, R. Kotagiri, and J. Bezdek, Approximate spectral clustering, Proceedings of 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD, Long, 11.5% acceptance rate), LNAI 5476, pp. 134-146, 2009.
L. Wang, X. Geng, J. Bezdek, C. Leckie, and R. Kotagiri, SpecVAT: enhanced visual cluster analysis, Proceedings of IEEE International Conference on Data Mining (ICDM, Regular, 9.6% acceptance rate), pp. 638-647, 2008.
L. Wang, X. Geng, C. Leckie, and R. Kotagiri, Moving shape dynamics: a signal processing perspective, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR, Poster, 27.9% acceptance rate), pp. 1649-1656, 2008.
X. Z. Wang, L. Wang and A. Wirth, Pattern discovery in motion time series via structure-based spectral clustering, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR, Poster, 27.9% acceptance rate), pp. 341-348, 2008.
L. Wang, X. Z. Wang, C. Leckie, and R. Kotagiri, Characteristic-based descriptors for motion sequence recognition, Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD, Long, 11.9% acceptance rate), LNCS 5012, pp. 369-380, 2008.
X. Geng, L. Wang, M. Li, Q. Wu, and K. Smith-Miles, Adaptive fusion of gait and face for human identification in video, Proceedings of IEEE Workshop on Applications of Computer Vision (WACV, Oral), pp. 1-6, 2008.
X. Z. Wang, A. Wirth and L. Wang, Structure-based statistical features and multivariate time series clustering, Proceedings of the 7th IEEE International Conference on Data Mining (ICDM, Regular, 7.5% acceptance rate), pp. 351-360, 2007.
L. Wang and D. Suter, Recognizing human activities from silhouettes: motion subspace and factorial discriminative graph model, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR, Poster, 23.4% acceptance rate), pp. 2518-2525, 2007.
T. J. Chin, L. Wang, K. Schindler, and D. Suter, Extrapolating learned manifolds for human activity recognition, Proceedings of the 14th IEEE International Conference on Image Processing (ICIP, Poster), I: 381-384, 2007.
L. Wang and D. Suter, Analyzing human movements from silhouettes using manifold learning, Proceedings of the 5th IEEE International Conference on Advanced Video- and Signal-based Surveillance (AVSS, Oral), p. 7, 2006.
L. Wang and D. Suter, Informative shape representations for human action recognition, Proceedings of the 18th International Conference on Pattern Recognition (ICPR, 15% acceptance rate), 2: 1266-1269, 2006.
L. Wang, Abnormal walking gait analysis using silhouette-masked flow histograms, Proceedings of 18th International Conference on Pattern Recognition (ICPR, Poster), III: 473-476, 2006.
L. Wang, From blob metrics to posture classification to activity profiling, Proceedings of the 18th International Conference on Pattern Recognition (ICPR, Poster), 4: 736-739, 2006.
L. Wang, H. Z. Ning, T. N. Tan, and W. M. Hu, Fusion of static and dynamic body biometrics for gait recognition, Proceedings of the 9th International Conference on Computer Vision (ICCV, Poster, 16.1% acceptance rate), 2: 1449-1454, 2003.