Zhen Zhang
Grant-Funded Researcher (C)
Australian Institute for Machine Learning - Projects
Faculty of Sciences, Engineering and Technology
Zhen Zhang is currently a Postdoctoral Researcher at the University of Adelaide, working with Prof. Qinfeng (Javen) Shi. Previously, he was a postdoctoral research fellow in the Department of Computer Science at the National University of Singapore under the supervision of Prof. Lee Wee Sun. He received a PhD in Computer Science from Northwestern Polytechnical University (Xi’an, China) under the supervision of Prof. Yanning Zhang. During Nov. 2012 to Dec. 2014, he was a visiting student at Australian Centre for Visual Technologies, University of Adelaide, under the supervision of Prof. Anton van den Hengel and Prof. Qinfeng (Javen) Shi. He completed his bachelor degree in Computer Science in 2010 at School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China, working with Prof. Yanning Zhang and Dr. Zhonghua Fu.
Zhen Zhang is currently a Postdoctoral Researcher at the University of Adelaide, working with Prof. Qinfeng (Javen) Shi, on causality, reinforcement learning and computer vision. Previously, he was a postdoctoral research fellow in the Department of Computer Science at the National University of Singapore under the supervision of Prof. Lee Wee Sun. He received a PhD in Computer Science from Northwestern Polytechnical University (Xi’an, China) under the supervision of Prof. Yanning Zhang. During Nov. 2012 to Dec. 2014, he was a visiting student at Australian Centre for Visual Technologies, University of Adelaide, under the supervision of Prof. Anton van den Hengel and Prof. Qinfeng (Javen) Shi. He completed his bachelor degree in Computer Science in 2010 at School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China, working with Prof. Yanning Zhang and Dr. Zhonghua Fu.
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Language Competencies
Language Competency Chinese (Mandarin) Can read, write, speak, understand spoken and peer review English Can read, write, speak, understand spoken and peer review -
Education
Date Institution name Country Title 2010 - 2017 Northwestern Polytechnical University China Ph.D -
Research Interests
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Journals
Year Citation 2024 Chen, L., Zhang, Y., Song, Y., Zhang, Z., & Liu, L. (2024). A Causal Inspired Early-Branching Structure for Domain Generalization. International Journal of Computer Vision, 132(9), 4052-4072.
2024 Zhang, X., Zhang, Z., Chinnici, A., Sun, Z., Shi, J. Q., Nathan, G. J., & Chin, R. C. (2024). Physics-informed data-driven unsteady Reynolds-averaged Navier-Stokes turbulence modeling for particle-laden jet flows. Physics of Fluids, 36(5), 23 pages.
2024 Li, H., Li, X., Wang, P., Zhang, Z., Davey, K., Shi, J. Q., & Qiao, S. -Z. (2024). Machine Learning Big Data Set Analysis Reveals C-C Electro-Coupling Mechanism. Journal of the American Chemical Society, 146(32), 22850-22858.
Scopus22024 Tan, Z., Li, X., Zhao, Y., Zhang, Z., Shi, J. Q., & Li, H. (2024). Machine Learning‐Driven Selection of Two‐Dimensional Carbon‐Based Supports for Dual‐Atom Catalysts in CO2 Electroreduction. ChemCatChem, 16(22), 9 pages.
2023 Zhao, Y., Li, H., Shan, J., Zhang, Z., Li, X., Shi, J. Q., . . . Li, H. (2023). Machine Learning Confirms the Formation Mechanism of a Single-Atom Catalyst via Infrared Spectroscopic Analysis. Journal of Physical Chemistry Letters, 14(49), 11058-11062.
Scopus22023 Zhang, X., Wei, W., Zhang, Z., Zhang, L., & Li, W. (2023). Milstein-driven neural stochastic differential equation model with uncertainty estimates. Pattern Recognition Letters, 174, 71-77.
Scopus32023 Yan, Q., Gong, D., Wang, P., Zhang, Z., Zhang, Y., & Shi, J. Q. (2023). SharpFormer: Learning Local Feature Preserving Global Representations for Image Deblurring. IEEE Transactions on Image Processing, 32, 2857-2866.
Scopus12 WoS1 Europe PMC12023 Meng, J., Wang, Z., Ying, K., Zhang, J., Guo, D., Zhang, Z., . . . Chen, S. (2023). Human Interaction Understanding With Consistency-Aware Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(10), 11898-11914.
Scopus3 Europe PMC12022 Zhou, S., Wang, X., ster, M., Li, B., Ye, C., Zhang, Z., . . . Bu, J. (2022). Direction-Aware User Recommendation Based on Asymmetric Network Embedding. ACM Transactions on Information Systems, 40(2), 1-23.
Scopus62022 Li, Z., Liu, Y., Zhang, Z., Pan, S., Gao, J., & Bu, J. (2022). Cyclic label propagation for graph semi-supervised learning. World Wide Web, 25(2), 703-721.
Scopus42021 Hu, Y., Zhang, Z., Yao, Y., Huyan, X., Zhou, X., & Lee, W. S. (2021). A bidirectional graph neural network for traveling salesman problems on arbitrary symmetric graphs. Engineering Applications of Artificial Intelligence, 97, 104061-1-104061-9.
Scopus26 WoS152020 Li, Z., Wang, H., Ding, D., Hu, S., Zhang, Z., Liu, W., . . . Zhang, J. (2020). Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation. Complexity, 2020, 1-13.
Scopus22020 Gong, D., Zhang, Z., Shi, Q., van den Hengel, A., Shen, C., & Zhang, Y. (2020). Learning deep gradient descent optimization for image deconvolution. IEEE Transactions on Neural Networks and Learning Systems, 31(12), 5468-5482.
Scopus74 WoS46 Europe PMC22019 Suwanwimolkul, S., Zhang, L., Gong, D., Zhang, Z., Chen, C., Ranasinghe, D. C., & Qinfeng Shi, J. (2019). An adaptive markov random field for structured compressive sensing. IEEE Transactions on Image Processing, 28(3), 1556-1570.
Scopus9 WoS62018 Wang, Z., Jin, J., Liu, T., Liu, S., Zhang, J., Chen, S., . . . Shao, Z. (2018). Understanding human activities in videos: A joint action and interaction learning approach. Neurocomputing, 321, 216-226.
Scopus132017 Yao, R., Xia, S., Zhang, Z., & Zhang, Y. (2017). Real-Time Correlation Filter Tracking by Efficient Dense Belief Propagation with Structure Preserving. IEEE Transactions on Multimedia, 19(4), 772-784.
Scopus41 WoS332014 Zhang, Z., & Zhang, Y. (2014). Variable kernel density estimation based robust regression and its applications. Neurocomputing, 134, 30-37.
Scopus9 WoS72013 Zhang, Z., Shi, Q., Zhang, Y., Shen, C., & Hengel, A. V. D. (2013). Constraint Reduction using Marginal Polytope Diagrams for MAP LP
Relaxations.2011 Sun, J. Q., Zhou, J., Zhang, Z., & Zhang, Y. P. (2011). Centroid location for space targets based on energy accumulation. Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 19(12), 3043-3048.
Scopus192011 Sun, J. Q., Zhou, J., Zhu, Y., & Zhang, Z. (2011). Smear removal of CCD camera in astronomic observation. Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 19(10), 2526-2532.
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Book Chapters
Year Citation 2025 Cai, Y., Liu, Y., Zhang, Z., & Shi, J. Q. (2025). CLAP: Isolating Content from Style Through Contrastive Learning with Augmented Prompts. In Lecture Notes in Computer Science (pp. 130-147). Springer Nature Switzerland.
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Conference Papers
Year Citation 2024 Liu, Y., Zhang, Z., Gong, D., Gong, M., Huang, B., van den Hengel, A., . . . Shi, J. Q. (2024). IDENTIFIABLE LATENT POLYNOMIAL CAUSAL MODELS THROUGH THE LENS OF CHANGE. In 12th International Conference on Learning Representations, ICLR 2024. Online: ICLR.
Scopus12023 Shen, S., Zhang, M., Chen, W., Bialkowski, A., & Xu, M. (2023). Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13938 LNCS (pp. 99-111). Online: Springer Nature Switzerland.
DOI2022 Yan, Q., Zhang, S., Chen, W., Liu, Y., Zhang, Z., Zhang, Y., . . . Gong, D. (2022). A Lightweight Network for High Dynamic Range Imaging. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2022-June (pp. 823-831). Online: IEEE.
DOI Scopus10 WoS12022 Perez-Pellitero, E., Catley-Chandar, S., Shaw, R., Leonardis, A., Timofte, R., Zhang, Z., . . . Park, C. Y. (2022). NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2022-June (pp. 1008-1022). Online: IEEE.
DOI Scopus28 WoS72022 Zhang, Z., Ng, I., Gong, D., Liu, Y., Abbasnejad, E. M., Gong, M., . . . Shi, J. Q. (2022). Truncated Matrix Power Iteration for Differentiable DAG Learning. In Advances in Neural Information Processing Systems Vol. 35 (pp. 13 pages). Online: Neural information processing systems foundation.
Scopus102021 Gu, C., Bu, J., Zhang, Z., Yu, Z., Ma, D., & Wang, W. (2021). Image Search with Text Feedback by Deep Hierarchical Attention Mutual Information Maximization. In MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia (pp. 4600-4609). New York, USA: ACM.
DOI Scopus222021 Gong, D., Zhang, Z., Shi, J. Q., & van den Hengel, A. (2021). Memory-augmented Dynamic Neural Relational Inference. In Proceedings 2021 IEEE/CVF International Conference on Computer Vision ICCV 2021 (pp. 11823-11832). Los Alamitos, CA, USA: IEEE.
DOI Scopus72020 Zhang, Z., Wu, F., & Lee, W. S. (2020). Factor graph neural network. In Thirty-fourth Conference on Neural Information Processing Systems, NeurIPS 2020 Vol. 2020-December (pp. 1-11). online: NIPS.
Scopus262020 Dupty, M. H., Zhang, Z., & Lee, W. S. (2020). Visual relationship detection with low rank non-negative tensor decomposition. In AAAI 2020 - 34th AAAI Conference on Artificial Intelligence Vol. 34 (pp. 10737-10744). online: AAAI.
Scopus42020 Su, X., Lee, W. S., & Zhang, Z. (2020). Multiplicative Gaussian Particle Filter. In S. Chiappa, & R. Calandra (Eds.), 23rd International Conference on Artificial Intelligence and Statistics (AISTAT) VOL 108 Vol. 108 (pp. 1-9). online: ADDISON-WESLEY PUBL CO.
Scopus12019 Zhang, Z., & Lee, W. S. (2019). Deep graphical feature learning for the feature matching problem. In Proceedings: 2019 International Conference on Computer Vision Vol. 2019-October (pp. 5086-5095). Los Alamitos, California: IEEE.
DOI Scopus57 WoS392018 Li, C., Zhang, Z., Lee, W. S., & Lee, G. H. (2018). Convolutional Sequence to Sequence Model for Human Dynamics. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 5226-5234). online: IEEE.
DOI Scopus263 WoS1562017 Zhang, Z., Shi, Q., McAuley, J., Wei, W., Zhang, Y., Yao, R., & Van Den Hengel, A. (2017). Solving constrained combinatorial optimization problems via MAP inference without high-order penalties. In Proceedings of the 31st AAAI Conference on Artificial Intelligence, AAAI 2017 (pp. 3804-3810). San Francisco: AAAI.
Scopus1 WoS12017 Zhang, Z., McAuley, J., Li, Y., Wei, W., Zhang, Y., & Shi, Q. (2017). Dynamic programming bipartite belief propagation for hyper graph matching. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017) Vol. 0 (pp. 4662-4668). online: AAAI Press.
DOI Scopus7 WoS42016 Zhang, Z., Shi, Q., McAuley, J., Wei, W., Zhang, Y., & Van Den Hengel, A. (2016). Pairwise matching through max-weight bipartite belief propagation. In Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2016) Vol. 2016 (pp. 1202-1210). Las Vegas, NV: IEEE.
DOI Scopus47 WoS242016 Rezatofighi, S., Milan, A., Zhang, Z., Shi, Q., Dick, A., & Reid, I. (2016). Joint probabilistic matching using m-best solutions. In Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2016) Vol. 2016-December (pp. 136-145). Las Vegas, NV: IEEE.
DOI Scopus23 WoS152016 Zhang, Z., Zhang, Y., Sun, J., & Sun, L. (2016). Image matching via higher order structures. In Proceedings of 2015 International Conference on Orange Technologies, ICOT 2015 (pp. 105-108). online: IEEE.
DOI2015 Tan, M., Shi, Q., Van Den Hengel, A., Shen, C., Gao, J., Hu, F., & Zhang, Z. (2015). Learning graph structure for multi-label image classification via clique generation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 4100-4109). Boston, MA: IEEE.
DOI Scopus42 WoS282015 Rezatofighi, S., Milan, A., Zhang, Z., Shi, Q., Dick, A., & Reid, I. (2015). Joint Probabilistic Data Association Revisited. In Proceedings of the 2015 IEEE International Conference on Computer Vision Vol. 2015 International Conference on Computer Vision, ICCV 2015 (pp. 3047-3055). Santiago, CHILE: IEEE.
DOI Scopus282 WoS1922015 Wang, Z., Zhang, Z., & Geng, N. (2015). A message passing algorithm for MRF inference with unknown graphs and its applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9006 (pp. 288-302). Springer International Publishing.
DOI Scopus12012 Zhang, Z., Zhang, Y., Yao, R., Li, H., & Zhu, Y. (2012). Generalized kernel density estimation based robust estimator and its application. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7202 LNCS (pp. 112-121). Springer Berlin Heidelberg.
DOI2012 Yao, R., Duan, F., Zhang, Z., & Zhang, Y. (2012). Faint moving object detection in optical astronomical image using a 2D-1D IUWT. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7202 LNCS (pp. 442-449). Springer Berlin Heidelberg.
DOI2011 Gao, J., Zhang, Z., Yao, R., Sun, J., & Zhang, Y. (2011). Smear radiometric correction algorithm in star images based on kernel density estimation. In Proceedings of SPIE - The International Society for Optical Engineering Vol. 8194 (pp. 819421). SPIE.
DOI Scopus12011 Gao, J., Zhang, Z., Yao, R., Sun, J., & Zhang, Y. (2011). A robust smear removal method for inter-frame Charge-Coupled Device star images. In Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011 Vol. 3 (pp. 1805-1808). IEEE.
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Preprint
Year Citation 2022 Liu, Y., Zhang, Z., Gong, D., Gong, M., Huang, B., Hengel, A. V. D., . . . Shi, J. Q. (2022). Identifying Weight-Variant Latent Causal Models.
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2024 Co-Supervisor Causal discovery and Out-of-Distribution generalization: sampling from posterior over causal graphs Doctor of Philosophy Doctorate Full Time Mr Nadhir Hassen 2024 Co-Supervisor Causality on Generative Model Doctor of Philosophy Doctorate Full Time Mr Jiaxin Wang 2024 Co-Supervisor Research on lightweight intelligent models based on deep learning: incorporating artificial intelligence on end devices Doctor of Philosophy Doctorate Full Time Ms Hongrong Cheng 2023 Co-Supervisor Causal Discovery on Videos for Scene Graph Generation Doctor of Philosophy Doctorate Full Time Mr Hamed Damirchi 2023 Co-Supervisor Leveraging Causality for Robust Multi-Source Domain Adaptation Doctor of Philosophy Doctorate Full Time Miss Tianjiao Jiang 2023 Co-Supervisor Domain Adaptation via Causal Representation Learning Doctor of Philosophy Doctorate Full Time Mr Yichao Cai
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