Google Scholar Profile

1. An Interpretable Cross-Attentive Multi-Modal MRI Fusion Framework for Schizophrenia Identification

   Ziyu Zhou, Anton Orlichenko, Gang Qu, Zening Fu, Zhengming Ding, Julia Stephen, Tony Wilson, Vince Calhoun, Yu-Ping Wang. NeuroImage: Reports, 6(2):100338, 2026.

2. BDCD: A Comprehensive Brain Disease Cell-Cell Communication Database

   Xinyi Liu, Citu Citu, Gang Qu, Wendao Liu, Nitesh Enduru, Andi Liu, Chia-Hao Tung, Zhongming Zhao. Database, 2026:baaf005, 2026.

3. DDS-UDA: Dual-Domain Synergy for Unsupervised Domain Adaptation in Joint Segmentation of Optic Disc and Optic Cup

   Yusong Xiao, Yuxuan Wu, Li Xiao, Gang Qu, Haiye Huo, Yu-Ping Wang. Medical Image Analysis, 111:104056, 2026.

4. Cooperative Multiplex GNN for High-Grade Glioma Survival Prediction from Preoperative Multi-Modal Radiomics-Based Brain Networks

   Ruike Cao, Xingcan Hu, Li Xiao, Gang Qu, Haiye Huo, Vince D. Calhoun, Yu-Ping Wang, Xiaoyan Sun. IEEE Transactions on Medical Imaging, early access, 2026.

5. Dual Attention Multi-View Multi-Task Learning for Cognitive Prediction from Brain Functional Connectivity

   Ruike Cao, Gang Qu, Li Xiao. Journal of Information and Intelligence, 2026.

6. BrainGeneBot: A Framework for Variant Prioritization and Generative Pretrained Transformer-Informed Interpretation Across Polygenic Risk Score Studies

   Gang Qu, Nitesh Enduru, Xinyi Liu, Xiaoqian Jiang, Zhongming Zhao. Briefings in Bioinformatics, 26(5):bbaf565, 2025.

7. A Deep Spatio-Temporal Architecture for Dynamic ECN Analysis with Granger Causality Based Causal Discovery

   Faming Xu, Yiding Wang, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Chen Qiao. Pattern Recognition, 172:112346, 2025.

8. Integrated Brain Connectivity Analysis with fMRI, DTI, and sMRI Powered by Interpretable Graph Neural Networks

   Gang Qu, Ziyu Zhou, Vince D. Calhoun, Aiying Zhang, Yu-Ping Wang. Medical Image Analysis, 103:103570, 2025.

9. Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks

   Gang Qu, Anton Orlichenko, Junqi Wang, Gemeng Zhang, Li Xiao, Kun Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang. IEEE Transactions on Medical Imaging, 43(4):1568-1578, 2024.

10. Explainable Spatio-Temporal Graph Evolution Learning with Applications to Dynamic Brain Network Analysis During Development

    Longyun Chen, Chen Qiao, Kai Ren, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang. NeuroImage, 298:120771, 2024.

11. A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development

    Yingying Wang, Chen Qiao, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang. IEEE Transactions on Biomedical Engineering, 71(12):3390-3401, 2024.

12. Multiview Hyperedge-Aware Hypergraph Embedding Learning for Multisite, Multiatlas fMRI Based Functional Connectivity Network Analysis

    Wei Wang, Li Xiao, Gang Qu, Vince D. Calhoun, Yu-Ping Wang, Xiaoyan Sun. Medical Image Analysis, 94:103144, 2024.

13. Latent Similarity Identifies Important Functional Connections for Phenotype Prediction

    Anton Orlichenko, Gang Qu, Gemeng Zhang, Binish Patel, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang. IEEE Transactions on Biomedical Engineering, 70(6):1979-1989, 2023.

14. Dynamic Weighted Hypergraph Convolutional Network for Brain Functional Connectome Analysis

    Junqi Wang, Hailong Li, Gang Qu, Kim M. Cecil, Jonathan R. Dillman, Nehal A. Parikh, Lili He. Medical Image Analysis, 87:102828, 2023.

15. Brain Functional Connectivity Analysis via Graphical Deep Learning

    Gang Qu, Wenxing Hu, Li Xiao, Junqi Wang, Yuntong Bai, Beenish Patel, Kun Zhang, Yu-Ping Wang. IEEE Transactions on Biomedical Engineering, 69(5):1696-1706, 2022.

16. Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies

    Li Xiao, Biao Cai, Gang Qu, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang. IEEE Transactions on Biomedical Engineering, 69(10):3039-3050, 2022.

17. Deep Learning in Neuroimaging: Promises and Challenges

    Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui, Vince D. Calhoun. IEEE Signal Processing Magazine, 39(2):87-98, 2022. (co-first author)

18. Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction

    Gang Qu, Li Xiao, Wenxing Hu, Junqi Wang, Kun Zhang, Vince D. Calhoun, Yu-Ping Wang. IEEE Transactions on Biomedical Engineering, 68(12):3564-3573, 2021.

19. Functional Network Estimation Using Multigraph Learning with Application to Brain Maturation Study

    Junqi Wang, Li Xiao, Wenxing Hu, Gang Qu, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang. Human Brain Mapping, 42:2880-2892, 2021.

20. Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition

    Wenxing Hu, Xianghe Meng, Yuntong Bai, Aiying Zhang, Gang Qu, Biao Cai, Gemeng Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang. IEEE Transactions on Medical Imaging, 40(5):1474-1483, 2021.

21. Graph Temporal Ensembling Based Semi-supervised Convolutional Neural Network with Noisy Labels for Histopathology Image Analysis

    Xiaoshuang Shi, Hai Su, Fuyong Xing, Yun Liang, Gang Qu, Lin Yang. Medical Image Analysis, 60:101624, 2020.

1. A Novel GNN Framework Integrating Neuroimaging and Behavioral Information to Understand Adolescent Psychiatric Disorders

   Wenjing Yu, Gang Qu, Young-geun Kim, Lin Xu, Aiying Zhang. Medical Imaging with Deep Learning (MIDL), 2025.

2. A Graph-Based Generative Adversarial Network Model for Inferring Task-State from Resting-State Functional Connectivity Networks

   Tao Jin, Hongzheng Guan, Li Xiao, Gang Qu, Yu-Ping Wang. ICASSP 2025, IEEE, pp. 1-5.

3. Spatio-Temporal Mapping Generative Adversarial Network for Functional Connectivity Network Reconstruction Across Brain Atlases

   Hongzheng Guan, Tao Jin, Li Xiao, Gang Qu, Yu-Ping Wang. ICASSP 2025, IEEE, pp. 1-5.

4. A Graph Deep Learning Model for the Classification of Groups with Different IQ Using Resting State fMRI

   Gang Qu, Wenxing Hu, Li Xiao, Yu-Ping Wang. SPIE Medical Imaging 2020, vol. 11317, 113170A.

5. Phenotype Guided Interpretable Graph Convolutional Network Analysis of fMRI Data Reveals Changing Brain Connectivity During Adolescence

   Anton Orlichenko, Gang Qu, Yu-Ping Wang. SPIE Medical Imaging 2022, vol. 12036, 1203612.

6. Thought Graph: Balancing Specificity and Uncertainty in LLM-Based Gene Set Annotation

   Kyle Cox, Gang Qu, Chi-Yang Hsu, Jiawei Xu, Yingtong Zhou, Zhen Tan, Mengzhou Hu, Tianlong Chen, Ziniu Hu, Zhongming Zhao, Ying Ding. IEEE 13th International Conference on Healthcare Informatics (ICHI), IEEE, 2025, pp. 462-470. (co-first author)

For a complete and up-to-date list, please visit my Google Scholar profile.