2002, PhD in Computer Vision and Pattern Recognition, National Lab of Pattern Recognition, Chinese Academy of Sciences, Beijing China

◆ 2019 – Present, Professor of Computer Science and Engineering Department, Southern University of Science and Technology, Shenzhen, China

◆ 2015 - 2019, Reader and Head of Internationalisation in Computing, School of Science and Engineering, University of Dundee

◆ 2010– 2015, Senior Lecturer, School of Computing, University of Dundee

◆ 2007 - 2010, Lecturer, School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast

◆ 2005 - 2007, Research Assistant, Department of Computer Science, Queen Mary University of London

◆ 2003 - 2005, Postdoc Research Fellow, INRIA Rhone-Alpes, France

◆ 2002 - 2003, Research Fellow, School of EEE, Nanyang Technological, University, Singapore

◆ 2017, Winning the international challenge on brain White Matter Hyperintensities (WMH) segmentation, MICCAI 2017, Quebec, Canada.

◆ 2015, Winning Endoscopic Vision Challenge on sub challenges of Polyp Localisation and Early Barret’s Cancer detection, MICCAI15, Munich.

◆ 2014, Winner (on both tasks of the contest) of the International Contest on Performance Evaluation of Indirect Immunofluorescence Image Analysis Systems with ICPR, Stockholm, Sweden.

◆ 2014, Best Performing Runner Up at the Brain Tumour Digital Pathology Challenge (MICCAI), Harvard Medical School (The first place using Organizer provided training images).

◆ 2014, Best Cancer Paper Award at Medical Image Understanding and Analysis Conference (MIUA), London, United Kingdom.

◆ 2008, Best Paper Award of International Machine Vision and Image Processing Conference, Ireland.

◆ 2006, Rank the first on 8 out of 10 categories of the second International PASCAL Visual Object Classification Challenge.

◆ 2005, Rank the first on 6 out of 8 categories of the first International PASCAL Visual Object Classification Challenge.

◆ 2002, Be awarded President Prize of Chinese Academy of Sciences, 2002.

1. Hugo J. Kuijf, & Jianguo Zhang, et al, Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities: Results of the WMH Segmentation Challenge, IEEE Transactions on Medical Imaging, 2019.(Summary of the Contest, and Winning method for the International challenge on brain White Matter Hyperintensities (WMH) segmentation, MICCAI 2017. See our NeuroImage paper for the details of the method)

2. Hu JF, Zheng WS, Ma LY, Wang G, Lai JH, and Zhang J, Early Action Prediction by Soft Regression, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 .

3. Hongwei Li, Gongfa Jiang, Ruixuan Wang, Jianguo Zhang, Zhaolei Wang, Wei-Shi Zheng, BjoernMenze, Fully Convolutional Network Ensembles for White Matter Hyperintensities Segmentation in MR Images, NeuroImage, 2018 (Winning method for the International challenge on brain White Matter Hyperintensities (WMH) segmentation, MICCAI-2017).

4. S. Bano, T. Suveges, J Zhang, S McKenna (2018), Multimodal, Egocentric Analysis of Focused Interactions, IEEE Access, 2018.

5. Sotirios Bisdas, Haocheng Shen, Steffi Thust, VasileiosKatsaros, George Stranjalis, Christos Boskos, Sebastian Brandner, and Jianguo Zhang, (2018) Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study, Scientific Report, Nature (Winning Methods for the Olea Innovators Contest prize for technology transfer).

6. Yan Li, Junge Zhang, Jianguo Zhang, Kaiqi Huang, Mixed Supervised Object Detection with Robust Objectness Transfer, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.

7. Daniel R Morales, Rob Flynn, Jianguo Zhang, Emmanuel Trucco, Jennifer K Quint, Kris Zutis (2018) External validation of ADO, DOSE, COTE and CODEX at predicting death in primary care patients with COPD using standard and machine learning approaches, Respiratory Medicine, Vol. 138, pp.150-155.

8. Siyamalan Manivannan, Wenqi Li, Jianguo Zhang, Emanuele Trucco, Stephen McKenna (2017), Structure Prediction for Gland Segmentation with Hand-Crafted and Deep Convolutional Features,  IEEE Trans. on Medical Imaging, 2017, DOI: 10.1109/TMI.2017.2750210.

9. Shaofan Lai, Weishi Zheng, Jiangfang Hu, Jianguo Zhang, Global-Local Temporal Saliency Action Prediction,  IEEE Transactions on Image Processing, 2017.

10. J. Hu, W. Zheng, J. Lai,  J Zhang, Jointly Learning Heterogeneous Features for RGB-D Activity Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol.39 (11), 2017, pp.2186-2200.

11. Siyamalan Manivannan, Wenqi Li, Shazia Akbar, Ruixuan Wang, Jianguo Zhang and Stephen J. McKenna An Automated Pattern Recognition System for Classifying Indirect Immunofluorescence Images of HEp-2 Cells and Specimens, Pattern Recognition, Volume 51, March 2016, p. 12-26 (Winning Methods for ICPR I3A Contest).

12. Wenqi Li, Maria Coats, Jianguo Zhang and Stephen McKenna (2015), Discriminating Dysplasia: optical tomographic texture analysis of colorectal polyps, Medical Image Analysis.

13. Xiaojuan Wang, Wei-Shi Zheng, Xiang Li, and Jianguo Zhang, Cross-scenario Transfer Person Re-identification, IEEE Trans Circuits and Systems for Video Technology.

Refereed Conference Publications (selected) 

1. Hongwei Li, Johannes C Paetzold, AnjanySekuboyina, Florian Kofler, Jianguo Zhang, Jan S Kirschke, BenediktWiestler, and BjoernMenze, DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis, MICCAI 2019.

2. Xionghui Wang, Jian-Fang Hu, Jianhuang Lai, Jianguo Zhang and Wei-Shi Zheng, Progressive Teacher-student Learning for Early Action Prediction, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019

3. Jiaxin Zhuang, JiabinCai, Ruixuan Wang, Jianguo Zhang, Weishi Zheng CARE: Class Attention to Regions of Lesion for Classification on Imbalanced DataMedical Imaging with Deep Learning Conference (MIDL -- in par with MICCAI) 2019

4. Jian-Fang Hu, Wei Shi Zheng, Jiahui Pan, Jian-Huang Lai, Jianguo Zhang (2018), Deep Bilinear Learning for RGB-D Action Recognition, European Conference on Computer Vision (ECCV).

5. Yan Li, Junge Zhang, jianguo Zhang, Kaiqi Huang, Discriminative Learning of Latent Features for Zero-Shot Recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

6. Hongwei Li, Jianguo Zhang, Mark Meuhlau, Jan KirschkeandBjoernMenze (2018), “Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation”, BrainLesin International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI).

7. Haocheng Shen, Ruixuan Wang, Jianguo Zhang, Stephen McKenna (2017), Boundary-aware Fully Convolutional Network for Brain Tumor Segmentation, MICCAI, 2017 (top conference in medical image analysis) https://doi.org/10.1007/978-3-319-66185-8_49

8. Weihua Chen, Xiaotang Chen, Jianguo Zhang, and Kaiqi Huang (2017), Beyond triplet loss: a deep quadruplet network for person re-identification, IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Associate Editor of IEEE Trans. On Multimedia (2019 – present)

Associate Editor of IET Computer Vision (2017 - present)

Associate Editor of EURASIP Advances in Signal Processing (2016-present)

Gest Editor of Pattern Recognition (2012)

Area Chair of BMVC (2010 –present)

PCs/reviews for ICCV, CVPR, ECCV, AAAI, IEEE PAMI, IJCV etc

Founding Chair and Organizer of VECTaR 2013 2012, 2011, 2010, 2009 (in conjunction with ICCV 2013, ECCV12, ICCV11 etc),