Personal profile
Personal profile
Dr. Junjie Zhang is currently an Associate Professor at the Department of Intelligent Science, School of Advanced Technology, Xi’an Jiaotong-Liverpool University (XJTLU), and he has been awarded the talent honor of Jiangsu Qinglan Project Youth Backbone Educator. He earned his Ph.D. in Information Technology from the University of Technology Sydney. Before joining XJTLU, he held a postdoctoral position at the Australian Institute for Machine Learning, The University of Adelaide, and served as a Lecturer at Shanghai University.
His research interests include computer vision, machine learning, and embodied AI, with a focus on multi-modal learning, remote sensing interpretation, and object perception. Dr. Zhang has published high-quality papers, including top-tier journals and conferences IEEE Trans, CVPR, ICCV, ECCV, AAAI etc. His research has been supported by both government and industry, including the NSFC, Jiangsu Science and Technology Fundamental Research Plan, and State Grid etc.
Research interests
- Core directions: Computer Vision, Multi-Modal Learning, Object Detection & Tracking
- Specialized focus: Aerial & Underwater Object Perception, Remote Sensing Interpretation, AI for Sports & Medical & Education
- Recruiting self-motivated students; contact via email for detailed information with your resume attached
- Research principle: We expect students perform long-term standardized research step by step, NOT opt for short-term resume polishing
- For Year2 & 3 student with machine learning project experiences, join the group through Pre->SURF ->Regular-> FYP
- For Year1 & 2 without prior project experiences, we recommend lay foundations first, you are welcome to query for learning materials
- 25-26 SEM2 SURF projects: Positions are now at full capacity
- 25-26 SEM2 FYP projects: Stay tuned
- 25-26 SEM2 FMP projects: Stay tuned
- Admission requirements: Comply with university policy; hold qualified research outputs (e.g., CV/ML/MM journal/conference publications, competition awards) and meet English proficiency standards
- Application process: Submit resume only after fulfilling prerequisites; applications will be fully reviewed; qualified candidates will receive an interview invitation within 2 weeks
- Available scholarships: 2 Fees-Only PhD scholarships, focusing on Object Perception & Multi-Modal Learning
Experience
Associate Professor, Department of Intelligent Science, SAT, XJTLU, 2024- Now
Lecturer, Shanghai University, 2021-2024
Postdoc, The University of Adelaide, 2018-2020
Teaching
INT101 Python for AI
INT204 Data Engineering
LIF001 (25-26 S2) Research-led and Project-based Learning
INT303 (25-26 S1) Big Data Analytics
INT402 (24-25 S1) Data Mining and Big Data Analytics
Related documents
Education/Academic qualification
PhD, University of Technology Sydney
Research areas
- Computer Vision
- Multi-Modal & Cross-Modal Learning
- Object Perception
Person Types
- Staff
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 11 Sustainable Cities and Communities
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Collaborations and top research areas from the last five years
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Research on edge intelligent offloading and caching optimisation in low-altitude economy networks
Hu, B. (PI), Xu, S. (Team member), Jia, D. (Team member), Zhang, J. (Team member), Zhang, W. (Team member), Pei, R. (Team member), Liu, H. (Team member), Wang, Z. (Team member), Huang, S. (Team member) & Qi, M. (Team member)
1/10/25 → 1/10/27
Project: Governmental Research Project
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Research on UAV multi-modal target perception method based on cross-view spatio-temporal collaboration
Zhang, J. (PI), Wu, F. (Team member), Guo, J. (Team member), Yin, D. (Team member), Tian, R. (Team member), Deng, B. (Team member) & Yang, S. (Team member)
1/09/25 → 31/08/28
Project: Governmental Research Project
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CodeQuest: An AI-Driven Gamified Learning Ecosystem for Python Programming Competency Development
Zhang, J. (PI) & Wu, F. (Team member)
1/07/25 → 30/06/28
Project: Internal Research Project
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AI-Driven Aerial Multi-modal Perception
Zhang, J. (PI)
1/07/25 → 31/07/28
Project: Internal Research Project
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CostDiff: Residual Diffusion-Based Cost Map Refinement for Open-Vocabulary Semantic Segmentation
Deng, B., Rao, Y., Wu, F. & Zhang, J., 2026, Pattern Recognition and Computer Vision - 8th Chinese Conference, PRCV 2025, Proceedings. Kittler, J., Xiong, H., Lin, W., Yang, J., Chen, X., Lu, J., Yu, J. & Zheng, W. (eds.). Springer Science and Business Media Deutschland GmbH, p. 120-134 15 p. (Lecture Notes in Computer Science; vol. 16283 LNCS).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Feasibility Study of Tabular Q-Learning for Multi-UAV Coverage Path Planning
Zhang, C., Owusu Boateng, G., Dong*, Q., Yu, L., Zhang, J. & Zhu, F., 2026, The 22nd International Wireless Communications & Mobile Computing Conference.Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Learning Compact Representations With an Information Bottleneck for Camouflaged Object Detection
Li, G., Zhang, J., Gao, R., Yuan, W., Jin, G. & Zeng, D., 2026, In: IEEE Transactions on Multimedia. 28, p. 360-372 13 p.Research output: Contribution to journal › Article › peer-review
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Multi-Proxy Quality-Aware Learning and Classifier Calibration for Few-Shot Incremental Fine-Grained Remote Sensing Classification
Jiang, H., Zhang, J., Xu, W., Zeng, D. & Zhang, J., 2026, (Accepted/In press) In: IEEE Transactions on Multimedia.Research output: Contribution to journal › Article › peer-review
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3DBench: A scalable benchmark for object and scene-level instruction-tuning of 3D large language models
Hu, T., Zhang, J., Rao, Y., Zeng, D., Yu, H. & Huang, X., Sept 2025, In: Neural Networks. 189, 107566.Research output: Contribution to journal › Article › peer-review