þ Master Supervisor

Research Areas

Multimodal Large Language Models, Medical Image Processing, Computer Vision and Natural Language Processing

Honors

Funding for high-level overseas returnees from Beijing in 2022.

Publications

[1] Xiaodan Zhang, Aozhe Jia, Junzhong Ji, Liangqiong Qu and Qixiang Ye. Intra- and Inter-Head Orthogonal Attention for Image Captioning. IEEE Transactions on Image Processing (TIP). 2025, 34: 594-607.

[2] Xiaodan Zhang, Yanzhao Shi, Junzhong Ji, Chengxin Zheng, Liangqiong Qu. MEPNet: Medical Entity-balanced Prompting Network for Brain CT Report Generation. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025.

[3] Chengxin Zheng, Junzhong Ji, Yanzhao Shi, Xiaodan Zhang*, Liangqiong Qu. See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2024: 16542–16552.

[4] Xiaodan Zhang, Shixin Dou, Junzhong Ji, Ying Liu, Zheng Wang. Co-occurrence Relationship Driven Hierarchical Attention Network for Brain CT Report Generation. IEEE Transactions on Emerging Topics in Computational Intelligence. 2024, 5(8):3643-3653.

[5] Xiaodan Zhang, Sisi Yang, Yanzhao Shi, Junzhong Ji, Ying Liu, Zheng Wang, Huimin Xu. Weakly guided attention model with hierarchical interaction for brain CT report generation, Computers in Biology and Medicine. 2023(167):107650.

[6] Yanzhao Shi, Junzhong Ji, Xiaodan Zhang*, Liangqiong Qu*, and Ying Liu. Granularity Matters: Pathological Graph-driven Cross-modal Alignment for Brain CT Report Generation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2023:6617–6630.

[7] Junzhong Ji, Zhuoran Du, Xiaodan Zhang*. Divergent-convergent Attention for Image Captioning. Pattern Recognition. 2021(115): 107928.

[8] Junzhong Ji, Cheng Xu, Xiaodan Zhang*, Boyue Wang, Xinhang Song. Spatio-temporal Memory Attention for Image Captioning. IEEE Transactions on Image Processing (TIP). 2020 (29): 7615-7628.

Personal Statement

 Xiaodan Zhang is an Associate Professor in the College of Computer Science and Beijing Institute of Artificial Intelligence, Beijing University of Technology. She obtained the joint Ph.D. degree from the University of Chinese Academy of Sciences and City University of Hong Kong in 2018. Her research focuses on critical theoretical and applied technologies in Artificial Intelligence, particularly Computer Vision and Natural Language Processing. She have published numerous papers in esteemed international journals and conferences, including IEEE TIP, Pattern Recognition, AAAI, ACM MM, EMNLP, and COLING.