個人信息

鄒愛笑，畢業于北京工業大學，計算機科學與技術專業，研究生學曆，工學博士學位。主要研究方向為：人工智能、深度學習、腦信息學編解碼、認知計算。博士期間曾參與國家自然基金項目、北京市自然科學基金、市教委重點項目等多項科研課題。在國内外重要學術期刊發表論文10餘篇，其中SCI期刊檢索論文4篇、EI檢索論文3篇、專利2項。

科研領域

人工智能、深度學習、腦信息學編解碼、認知計算等領域

代表性論文

1.Aixiao Zou, Junzhong Ji, Minglong Lei, Jinduo Liu, Yongduan Song. Exploring Brain Effective Connectivity Networks Through Spatiotemporal Graph Convolutional Models. IEEE Transactions on Neural Networks and Learning Systems, 2022, DOI: 10.1109/TNNLS.2022.322.1617.

2. Junzhong Ji, Aixiao Zou, Jinduo Liu, Cuicui Yang, Xiaodan Zhang, Yongduan Song. A Survey on Brain Effective Connectivity Network Learning. IEEE Transactions on Neural Networks and Learning Systems, 2023，34(4), 1879-1899.

3.Aixiao Zou, Junzhong Ji. Learning brain effective connectivity networks via controllable variational autoencoder. 2021 IEEE International Conference on Bioinformatics and Biomedicine, Houston, TX, USA, 2021.

4. Junzhong Ji, Jinduo Liu, Aixiao Zou, Aidong Zhang. ACOEC-FD: Ant Colony Optimization for Learning Brain Effective Connectivity Networks From Functional MRI and Diffusion Tensor Imaging. Frontiers in Neuroscience,2019, 13:1290.

5. 冀俊忠,鄒愛笑,劉金铎. 基于功能磁共振成像的人腦效應連接網絡識别方法綜述.自動化學報,2021, 47(2): 278-296.

科研項目

[1]校級青年科研基金項目：基于fMRI數據深度時空特征學習的腦效應網絡識别方法研究，主持，2022-2025