Zheng Zhang
Professor, Doctoral Supervisor
Cheung Kong Young Scholar (教育部青年长江学者)
Harbin Institute of Technology, Shenzhen, China
[Google Scholar] [Homepage in Chinese]

Area Chair: ICML/NeurIPS/ICLR/CVPR/MM
Associate Editor: IEEE TAFFC/IEEE JBHI
Drawing

Dr. Zheng Zhang is a faculty member at School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China, and also holds an adjunct position at Peng Cheng Laboratory, Shenzhen, China. He is the deputy director of the Shenzhen Key Laboratory of Visual Object Detection and Recognition, Shenzhen, China. Dr. Zhang is the Big Media Intelligence (BMI) Research Group Leader.

Openings: I am continuously looking for highly motivated Ph.D. students and postdoctoral researchers to work on machine learning, computer vision, and multimedia. Please send me your CV if interested. I can supervise Ph.D. students affiliated with the Harbin Institute of Technology as well as Peng Cheng Laboratory. You also may refer to my BMI research group for detailed information.
招生：欢迎优秀硕士生报考，2025年仍有部分名额~


Biography

Zheng Zhang received his Ph.D. from the Harbin Institute of Technology (HIT), supervised by Prof. Yong Xu (Changjiang Professorship). During his Ph.D., he visited the Institute of Automation of Chinese Academy of Sciences, advised by Prof. Cheng-Lin Liu (IEEE Fellow). Following his doctoral studies, he joined The Hong Kong Polytechnic University (PolyU) as an Assistant Researcher and later became a Postdoctoral Research Fellow in the Data Science Group at The University of Queensland (UQ), Australia, supervised by Prof. Helen Huang. He was also fortunately mentored by Prof. Heng Tao Shen (Member of Academia Europaea, ACM/IEEE Fellow) and Prof. Ling Shao (IEEE Fellow). Since 2019, Dr. Zhang has been a faculty member at the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China.

Dr. Zhang's research focuses on Machine Learning and Multimedia, with specific interests in Multimodal Learning, Resource-Efficient Deep Learning, and AI Security. He has published over 100 papers in leading international journals and conferences. He has received prestigious recognitions such as the Distinguished Ph.D. Dissertation Award from CIE (2019), Outstanding Young Research Achievement Award from CAAI (2019), Excellent Young Scientists Fund from Shenzhen (2023), and Young Pearl River Scholars of Guangdong Province (2023). His innovative multimedia systems have been featured by prominent media outlets such as UN COP26, Xinhua News, and have been successfully transferred to leading industries like Tencent, Alibaba Group, Huawei, ICBC, and SZIDC. He has been recognized among the 'World’s Top 2% Scientists' for several consecutive years and is a Senior Member of IEEE and CCF.

Dr. Zhang is/was an editorial board member of several prominent journals, including IEEE T-AFFC, IEEE J-BHI, Elsevier INS, Elsevier INFFUS, Elsevier IP&M, and Elsevier ESWA. He has regularly contributed as an Area Chair or Senior PC for numerous top-tier conferences, such as ICML, NeurIPS, CVPR, ICLR, ACM MM, AAAI, and IJCAI. Additionally, he has played key roles in organizing international conferences, including ADMA 2021 and 2023, ACM Multimedia Asia 2021, and other significant events.

Research Interests


Publications [Selected Pub] [Full Pub]

Books:
  1. Zheng Zhang, Binary Representation Learning on Visual Images, ISBN: 978-981-97-2111-5, Springer Nature, Jun. 2024. [Link]
  2. Zheng Zhang, Yong Xu, Guangming Lu, Structural Representation Learning for Data Analysis, Posts & Telecom Press, China, ISBN: 978-7-115-58401-4, 2022. [Link]
  3. 张海军, 马江虹, 张正, 数据结构与智能算法, 清华大学出版社, 2024. (本科生教材)
  4. 张永兵, 张健, 张正, 王鸿鹏, 计算病理学, 清华大学出版社, 2024.
  5. Lei Zhu, Jingjing Li, Zheng Zhang, Dynamic Graph Learning for Dimension Reduction and Data Clustering, Synthesis Lectures on Computer Science (SLCS), ISBN: 978-3-031-42312-3, Springer Nature, 2023.
  6. Xiaochun Yang, Chang-Dong Wang, Saiful Islam, Zheng Zhang (Eds.), The 16th International Conference on Advanced Data Mining and Applications, ADMA 2020, Foshan, China, Nov. 12-14 2020, Springer LNAI, vol. 12447, ISBN: 978-3-030-65389-7, 2020.
  7. Shuihua Wang, Zheng Zhang, Yuan Xu (Eds.), The IoT and Big Data Technologies for Health Care, The second EAI International Conference, IoTCARE 2021, October 18-19, 2021, Springer LNICS, Social Informatics and Telecommunications Engineering, 2021.

Journal paper:
  1. Z. Zhang, L. Liu, F. Shen, H. T. Shen, L. Shao, Binary Multi-View Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(7):1774-1782, 2019. (CCF A) [Paper][Link][Code]
  2. Z. Zhang✉, X. Yuan, L. Zhu, J. Song, L. Nie, BadCM: Invisible Backdoor Attack against Cross-Modal Learning, IEEE Transactions on Image Processing (TIP), 33: 2558-2571, 2024. (CCF A)[Link][Code]
  3. X. Yuan, Z. Zhang✉, X. Wang, L. Wu, Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval, IEEE Transactions on Information Forensics and Security (TIFS), 18: 4681-4694, 2023. (CCF A) [Link][Code]
  4. Z. Zhang, H. Luo, L. Zhu, G. Lu, H. T. Shen, Modality-Invariant Asymmetric Networks for Cross-Modal Hashing, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 35, no. 5, pp. 5091-5104, 2023. (CCF A) [Link][Code]
  5. Q. Wu, Z. Zhang✉, Y. Liu, J. Zhang, L. Nie, Contrastive Multi-bit Collaborative Learning for Deep Cross-modal Hashing, IEEE Transactions on Knowledge and Data Engineering (TKDE), 36 (11): 5835-5848, 2024. (CCF A) [Link][Code]
  6. H. Luo, Z. Zhang✉, L. Nie, Contrastive Incomplete Cross-modal Hashing, IEEE Transactions on Knowledge and Data Engineering (TKDE), 36 (11): 5823-5834, 2024. (CCF A) [Link][Code]
  7. J. Wen, Z. Zhang✉, Z. Zhang, L. Fei, M. Wang, Generalized Incomplete Multiview Clustering With Flexible Locality Structure Diffusion, IEEE Transactions on Cybernetics (TCYB), 51(1): 101-114, 2021. [Link][Code]
  8. J. Wen✟, Z. Zhang✟, L. Fei, B. Zhang, Y. Xu, Z. Zhang, J. Li, A Survey on Incomplete Multiview Clustering, IEEE Transactions on Systems, Man and Cybernetics: Systems (TSMCA), vol. 53, no. 2, pp. 1136-1149, 2023. [Link][Suppl Doc][Code]
  9. Z. Zhang✉, X. Wang, G. Lu, F. Shen, L. Zhu, Targeted Attack of Deep Hashing via Prototype-supervised Adversarial Networks, IEEE Transactions on Multimedia (TMM), vol. 24, pp. 3392-3404, 2022. [Link][Code]
  10. A. Lin, B. Chen, J. Xu, Z. Zhang✉, G. Lu, DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation, IEEE Transactions on Instrumentation & Measurement (TIM), vol. 71, pp. 1-15, 2022. [Link][Code] (Top 3 Most Popular Paper, Jul. 2022-now)

Conference paper:
  1. H. Luo, Z. Zhang✉, Y. Luo, Exploiting Descriptive Completeness Prior for Cross Modal Hashing with Incomplete Labels, in Proc. of The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. (CCF A) [Link][Code]
  2. Y. Liu, J. Wen✉, C. Liu, X. Fang✉, Z. Li, Y. Xu, Z. Zhang✉, Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition, in Proc. of The Forty-first International Conference on Machine Learning (ICML), 2024. (CCF A) [Link][Code]
  3. J. Xu, Y. Ren, X. Wang, L. Feng, Z. Zhang, G. Niu, X. Zhu, Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (CCF A) [Link][Code]
  4. Y. Mo, F. Nie, P. Hu, H. T. Shen, Z. Zhang✉, X. Wang✉, X. Zhu✉, Self-supervised Heterogeneous Graph Learning: a Homogeneity and Heterogeneity Perspective, in Proc. of The Twelfth International Conference on Learning Representations (ICLR), 2024. [Link][Code]
  5. B. Chen, S. Fu, Y. Liu, J. Pan, G. Lu, Z. Zhang✉, CariesXrays: Enhancing Caries Detection in Hospital-scale Panoramic Dental X-rays via Feature Pyramid Contrastive Learning, in Proc. of The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF A) [Link][Code]
  6. Y. Liu, Q. Wu, Z. Zhang✉, J. Zhang, G. Lu, Multi-Granularity Interactive Transformer Hashing for Cross-modal Retrieval, in Proc. of The 31st ACM International Conference on Multimedia (ACMM), 2023. (CCF A, Oral) [Link][Code]
  7. X. Wang, Z. Zhang✉, G. Lu, Y. Xu, Targeted Attack and Defense for Deep Hashing, in Proc. of The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 2298-2302, 2021. (CCF A) [Link][Code]
  8. X. Wang✟, Z. Zhang✟✉, B. Wu, F. Shen, G. Lu, Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing, in Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16357-16366, 2021. (CCF A) [Link][Code]
  9. J. Wen✟, Z. Zhang✟✉, Z. Zhang✉, L. Zhu, L. Fei, B. Zhang, Y. Xu, Unified Tensor Framework for Incomplete Multi-view Clustering and Missing-view Inferring, in Proc. of The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 35(11), pp. 10273-10281, 2021. (CCF A) [Code]
  10. Y. Luo, Z. Huang, Z. Zhang✉, Z. Wang, M. Baktashmotlagh, Y. Yang, Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks, in Proc. of The Thirty-Four AAAI Conference on Artificial Intelligence (AAAI), New York, USA, pp. 5021-5028, 2020. (CCF A) [Acceptance Rate: 20.6%] [Link][Code]

Professional Activities

Journal Editorial Board Membership

Conference Technical Program Committee

Journal Reviewer (20+ IEEE/ACM Trans.):

Research Group

Current Research Students Former Graduate Students (2019- )
Former Undergraduate Students (2020-2021)