1. Hui Liu, Yanfeng Wu, Tingting Xue, Zhe Du, Jun Xu, and Tao Jiang, Machine learning-assisted parametric analysis and multi-criteria optimization of building performance: A case study on indoor environmental quality and energy efficiency, Energy Conversion and Management, vol. 349, 120825, 2026.[Link to paper]

2. Mingxin Liu, Chengfei Cai, Depin Chen, Jun Li, Jinze Li, Wenlong Ming, and Jun Xu, Data- and Knowledge-Driven Multimodal Learning in Computational Pathology: A Comprehensive Survey, EngMedicine, 2026.[Link to paper]

3. Junjie Zhu, Jin Li, Shen Zhao, Yiyan Deng, Yongming Miao, Jun Xu, Adapting LLMs for biomedical natural language processing: a comprehensive benchmark study on fine-tuning methods, The Journal of Supercomputing, 2026. [Link to paper]

4. Qinhao Guo, Haoyu Cui, Yangyang Zhang, Shaoxian Tang, Weicheng Yan, Xiaoyan Zhou, Hongmei Ding, Jinhua Zhou, Xingzhu Ju, Zheng Feng, Jun Zhu, Fang Bai, Yanping Zhong, Haiming Li, Jun Xu, Xiaohua Wu, Xiangxue Wang, and Hao Wen, An Interpretable Deep Learning Model for Predicting Endometrial Cancer Molecular Subtypes from H&E-Stained Slides, npj Precision Oncology, 2026. [Link to paper]

5. Yuemei Luo, Yuan Li, Jiaxue Mei, Jun Xu, Linbo Liu, Xiaohua Qian, Automatic Identification of Retinopathy from Optical Coherence Tomography Images via a Similarity Matching Approach, 2026 IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP 2026), 4-8 May 2026, Barcelona, Spain. [Link to paper]