温旭云，南京航空航天大学计算机科学与技术学院副教授，中山大学和美国北卡罗来纳大学教堂山分校计算机科学与技术专业联合培养博士。主要研究方向为人工智能与脑科学交叉领域，包括：脑启发的大模型机理解析、基于影像分析的脑发育智能模型构建等，已在相关领域发表学术论文40余篇，包括：IEEE TMI、IEEE TEC、IEEE TNSRE、NeuroImage、Human Brain Mapping、Cerebral Cortex、MICCIA、IEEE BIBM、ISBI等。担任IEEE TMI、IEEE TBME、IEEE TIM、IEEE TNNLS、Brain Research、Frontier in Neuroscience等国际期刊审稿人。主持和完成国家自然科学基金青年和面上项目、科技创新2030“脑科学与类脑研究”婴幼儿重大项目子课题、和南京航空航天大学“人工智能”专项等；参与国家自然科学基金重点项目、以及基础加强计划技术领域基金重点项目等。获江苏省“双创博士”称号，现任中国图像图形学会脑图谱专业委员会委员、江苏省人工智能学会医学图像处理专委会委员等。担任SCI期刊Congenital Heart Disease青年编委。

可招聘计算机科学与技术和计算机技术的研究生，今年还有名额，欢迎对人工智能和脑科学交叉学科感兴趣的学生申报！课题组经费充足，支持学生参加国际和国内学术会议！

节选期刊论文：

1. Gong, P., Wang, P., Zhou, Y., Wen, X. (2024). TFAC-Net: A Temporal-Frequential Attentional Convolutional Network for Driver Drowsiness Recognition With Single-Channel EEG. IEEE Transactions on Intelligent Transportation Systems. 

2. Ma, K., Wen, X. (2023). Ordinal Pattern Tree: A New Representation Method for Brain Network Analysis. IEEE Transactions on Medical Imaging. 

3. Zhou, Y., Wang, P., Gong, P., Wei, F., Wen, X., Wu, X., Zhang, D. (2023). Cross-subject Cognitive Workload Recognition Based on EEG and Deep Domain Adaptation. IEEE Transactions on Instrumentation and Measurement, 72, 2518912.

4. Wen, X., Cao, Q., Zhao, Y., Wu, X., Zhang, D. (2024). D-MHGCN: An End-to-End Individual Behavioral Prediction Model Using Dual Multi-Hop Graph Convolutional Network. IEEE Journal of Biomedical and Health Informatics. 

5. Wen, X., Cao, Q., Zhang, D. (2024). Multi-Scale FC-based Multi-Order GCN: A Novel Model for Predicting Individual Behavior from fMRI. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 

6. Wen, X., Yang, M., Qi, S., Wu, X., Zhang, D. (2024). Automated individual cortical parcellation via consensus graph representation learning. NeuroImage, 293, 120616. 

7. Wen, X., Zhang, H., Li, G., Liu, M., Yin, W., Lin, W., Shen, D. (2019). First-Year Development of Modules and Hubs in Infant Brain Functional Networks. Neuroimage, 185, 222-235. 

8. Wen, X., Chen, W. N., Lin, Y., Gu, T., Zhang, H., Li, Y., Zhang, J. (2017). A Maximal Clique Based Multiobjective Evolutionary Algorithm for Overlapping Community Detection. IEEE Transactions on Evolutionary Computation, 21(3), 363-377.

节选会议论文：

1. Zhao, Y., Nie, D., Chen, G., Wu, X., Zhang, D., Wen, X. (2024) TARDRL: Task-Aware Reconstruction for Dynamic Representation Learning of fMRI. International Conference on Medical Image Computing and Computer-Assisted Intervention. (CCF B，医学影像顶会)

2. Xue, P., Nie, D., Zhu, M., Yang, M., Zhang, H., Zhang, D., Wen, X. (2024) WSSADN: A Weakly Supervised Spherical Age-Disentanglement Network for Detecting Developmental Disorders with Structural MRI. International Conference on Medical Image Computing and Computer-Assisted Intervention. (CCF B，医学影像顶会)

3. Lin, Y., Nie, D., Liu, Y, Yang, M., Zhang, D., Wen, X. (2023). Multi-Target Domain Adaptation with Prompt Learning for Medical Image Segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention. (CCF B，医学影像顶会)

4. Yang, M., Hsu, L. M., Qi, S., Zhang, D., Wen, X. (2023). A Multi-View Clustering-Based Method for Individual and Group Cortical Parcellations with Resting-State fMRI. IEEE 20th International Symposium on Biomedical Imaging (医学影像顶会).

5. Cao, Q., Wen, X. (2023) DouGNN: An End-to-End Deep Learning Framework for Predicting Individual Behaviors from fMRI Data. IEEE 2nd International Conference on Image Processing, Computer Vision and Machine Learning (ICICML).

6. Ma, K., Wen, X., Zhu, Q., Zhang, D. (2023). Positive Definite Wasserstein Graph Kernel for Brain Disease Diagnosis. International Conference on Medical Image Computing and Computer-Assisted Intervention (CCF B，医学影像顶会).

7. Ma, K., Wen, X., Zhu, Q., Zhang, D. (2022). Optimal Transport Based Ordinal Pattern Tree Kernel for Brain Disease Diagnosis. International Conference on Medical Image Computing and Computer-Assisted Intervention (CCF B， 医学影像顶会).