马昊，1995年生，博士，准聘副教授，硕士生导师，毕业于北京交通大学。研究方向：认知计算、深度学习、医学智能。近年来在《IEEE Transactions on Neural Networks and Learning Systems》、《IEEE Journal of Biomedical and Health Informatics》以及《International Conference on Medical Image Computing and Computer Assisted Intervention》等国内外知名期刊与国际会议发表论文8篇，其中中科院一区期刊3篇、CCF-B以及中科院二区期刊2篇、中科院三区3篇，Google学术引用50次，参与完成国家级项目3项。
招生信息：
欢迎具有扎实数学功底和较好深度学习基础且对脑科学有兴趣的计算机科学与技术专业的同学与我联系。
邮箱：domius@nxu.edu.cn
科研情况：
1.基于静息状态功能磁共振成像(fMRI)的个体认知参数定量评估研究，国家自然科学基金面上项目（61773048），参与，2018.1–2021.12
2.基于自然范式fMRI的新型脑功能静态及动态属性表征技术研究，国家自然科学基金面上项目（62276021），参与，2023.1–2026.12
3.融合器智能匹配技术研究及AI辅助OLIF术前规划系统构建，国家重点研发计划课题（2022YFC2407201），参与，2022.11-2025.10
科研成果：
1.Hao Ma, Fan Wu, Yun Guan, Le Xu, Jiangcong Liu, Lixia Tian*. BrainNet with connectivity attention for individualized predictions based on multi-facet connections extracted from resting-state fMRI data. Cognitive Computation, 2023, 15: 1566-1580.(JCR Q2 区，中科院三区2023，IF 4.300).
2.Hao Ma, Yongkang Xu, Lixia Tian*.RS-MAE: Region-state masked autoencoder for neuropsychiatric disorder classifications based on resting-state fMRI. IEEE Transactions on Neural Networks and Learning Systems, 2025, 36 (6): 10707-10720.(JCR Q1 区，中科院一区，Top期刊, 2025，IF 10.200).
3.Fan Wu,Hao Ma, Yun Guan, Lixia Tian*. Manifold-based unsupervised metric Learning, with applications in individualized predictions based on functional connectivity. Biomedical Signal Processing and Control, 2023, 79: 104081.(JCR Q1区，中科院二区，2023，IF 6.700).
4.Yun Guan,Hao Ma,Jiangcong Liu,Zhang Yang, Lixia Tian*. The abilities of movie-watching functional connectivity in individual identifications and individualized predictions. Brain Imaging and Behavior, 2023, 17(6): 628-638.(JCR Q2区，中科院三区，2023，IF 2.400).
5.Xiaoxi Tian,Hao Ma, Yun Guan, Le Xu, Jiangcong Liu, Lixia Tian*. Transformer^3: A pure transformer framework for fMRI-based representations of human brain function. IEEE Journal of Biomedical and Health Informatics. 2025, 29: 468-481(JCR Q1区，中科院一区，Top期刊, 2023，IF 6.700).
6.Le Xu,Hao Ma, Yun Guan, Jiangcong Liu, Huifang Huang, Yang Zhang, Lixia Tian*. A Siamese network with node convolution for individualized predictions based on connectivity maps extracted from resting-state fMRI data. IEEE Journal of Biomedical and Health Informatics, 2023, 27: 5418-5429(JCR Q1区，中科院一区，Top期刊, 2023，IF 6.700).
7.Mengting Ye,Jiangcong Liu,Yun Guan,Hao Ma, Lixia Tian*. Are inter-subject functional correlations consistent across different movies?[J]. Brain Imaging and Behavior, 2023, 17(1): 44-53.(JCR Q2区，中科院三区，2023，IF 2.400).
8.Jiangcong Liu, Le Xu, Yun Guan,Hao Ma, Lixia Tian*. CL-ADDA: Contrastive learning with amplitude-driven data augmentation for fMRI-Based individualized predictions. MICCAI. 2023: 384-393. (医学图像处理顶会)
