Junfeng Xia

About

I am Junfeng Xia, a master's student in Biomedical Engineering at Southern University of Science and Technology, advised by Prof. Quanying Liu. Before joining SUSTech, I received my B.Eng. in Computer Science and Technology from Zhengzhou University, where I was advised by Prof. Qidong Liu.

My research interests include neuroscience representation learning and the information architecture of the brain.

News

  • Jun 2026Brain-DiT was accepted by the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).
  • Jun 2026BrainWorld was released on arXiv.
  • Jun 2026FlexiBrain was released on arXiv.
  • Apr 2026Omni-fMRI was accepted by the International Conference on Machine Learning (ICML).
  • Jun 2025SLIM-Brain was released on arXiv.
  • Jun 2025I was selected for the Croucher Summer Course in Computational Neuroscience at the Chinese University of Hong Kong.
  • May 2025Our work on ultralow-power ion-gel nanofiber artificial synapses for enhanced working memory was published in Advanced Materials.
  • Sep 2024Our work on A Genetic Algorithms for Optimizing Structural Brain Network Across Cognitive Tasks was published in China Automation Congress.
  • Jun 2024Our work on Uncovering Cognitive Taskonomy through Transfer Learning in Masked Autoencoder-based fMRI Reconstruction was published in the International Workshop on Human Brain and Artificial Intelligence (HBAI), IJCAI.
  • Jun 2023I began research training at Southern University of Science and Technology as a visiting student.

Publications

* denotes equal contribution.

  • Junfeng Xia, Wenhao Ye, Xuanye Pan, Xinke Shen, Mo Wang, and Quanying Liu. Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), accepted, 2026. First author.
  • Junfeng Xia, Wenhao Ye, Junxiang Zhang, Xuanye Pan, Mo Wang, and Quanying Liu. BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics. arXiv, 2026. First author.
  • Mo Wang*, Junfeng Xia*, Wenhao Ye, Enyu Liu, Kaining Peng, Jianfeng Feng, Quanying Liu, and Hongkai Wen. SLIM-Brain: A Data- and Training-Efficient Foundation Model for fMRI Data Analysis. arXiv:2512.21881, 2025. Co-first author.
  • Mo Wang*, Wenhao Ye*, Junfeng Xia*, Minghao Xu, Hongkai Wen, and Quanying Liu. FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI. arXiv:2606.11500, 2026. Co-first author.
  • Mo Wang*, Wenhao Ye*, Junfeng Xia, Junxiang Zhang, Xuanye Pan, Minghao Xu, Haotian Deng, Hongkai Wen, and Quanying Liu. Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model. International Conference on Machine Learning (ICML), accepted, 2026.
  • Yuanxia Chen, Junfeng Xia, Youzhi Qu, Hongjie Zhang, Tingting Mei, Xinyi Zhu, Guoheng Xu, Dongyang Li, Li Wang, Quanying Liu, and Kai Xiao. Ephaptic Coupling in Ultralow-Power Ion-Gel Nanofiber Artificial Synapses for Enhanced Working Memory. Advanced Materials, 37(16), 2419013, 2025.
  • Youzhi Qu*, Junfeng Xia*, Xinyao Jian, Wendu Li, Kaining Peng, Zhichao Liang, Haiyan Wu, and Quanying Liu. Uncovering Cognitive Taskonomy through Transfer Learning in Masked Autoencoder-based fMRI Reconstruction. International Workshop on Human Brain and Artificial Intelligence (HBAI), IJCAI, 35-50, 2024. Co-first author.
  • Youzhi Qu, Wendu Li, Junfeng Xia, Jiahao Tang, Kaining Peng, Zhichao Liang, Haiyan Wu, and Quanying Liu. A Genetic Algorithms for Optimizing Structural Brain Network Across Cognitive Tasks. China Automation Congress, 5210-5215, 2024.

Books

  • Human Brain Intelligence and Artificial Intelligence. Tsinghua University Press, 2025.

Service

Teaching

  • Teaching Assistant, Machine Learning and Medical Engineering Applications, SUSTech, Shenzhen, 2025. Instructor: Prof. Quanying Liu.

Academic Activities

  • Visiting Student, Neural Computing and Control Lab, Southern University of Science and Technology, 2023-2024.
  • Selected participant, Croucher Summer Course in Computational Neuroscience, Chinese University of Hong Kong, Jun. 2025.