Dr. Qi Zhu （朱旗教授）

Dr. Qi Zhu

College of Artificial Intelligence,
Nanjing University of Aeronautics and Astronautics (NUAA)

Email: zhuqi@nuaa.edu.cn
Address: No. 29 Jiangjun Avenue, Jiangning District, Nanjing, China
Office: Room 11319, Building 1

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NUAA College of Artificial Intelligence
Short Bio Education Research Selected Publications Honors & Awards Professionals Research Fund Resources
Short Bio [Top]

Dr. Qi Zhu is a Professor and PhD Supervisor at the College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics (NUAA), where he also serves as Associate Dean. He is both a National-level Young Talent and a Jiangsu Province '333' High-level Talent. He received his BSc, MSc, and PhD from the Harbin Institute of Technology, and was awarded the Academic Scholarship for Doctoral Candidates, Ministry of Education, China.

His research interests include brain network analysis, brain-computer interaction, and cross-disciplinary AI applications. He has published over 200 papers, including more than 50 papers in IEEE/ACM Transactions and CCF-A conferences, in venues such as IEEE TMI, IEEE TIFS, IEEE TAFFC, IEEE TIP, IEEE TCBB, Nature Communications, NeurIPS, IJCAI, ACM MM, CVPR, and MICCAI. He has received 3 provincial/ministerial science and technology awards and holds over 30 authorized patents.

He has led 10+ research projects, including 3 grants from the National Natural Science Foundation of China, a defense application promotion project, a sub-project of a National Key R&D Program, and a Jiangsu Natural Science Foundation grant.

If you are interested in related research, please feel free to contact Dr. Zhu by email.

How to contact me:

Education [Top]
Selected Publications ｜ Google Scholar [Top]
200+ papers; 50+ in IEEE/ACM Transactions & CCF-A venues, including IEEE TMI, IEEE TIFS, IEEE TAFFC, IEEE TIP, IEEE TCBB, Nature Communications, NeurIPS, IJCAI, ACM MM, CVPR, MICCAI; 3 provincial/ministerial science & technology awards; 30+ patents.

A selection of recent publications (listed in the order presented on the official homepage; numbering corrected from the source). "*" denotes corresponding author.

1. Brain Network Analysis（脑网络分析）
Framework figure

Spatio-Temporal Hypergraph Attention Networks for Brain Disease Analysis

Chaojun Li, Peiliang Gong, Shengrong Li, Chunwei Tian, Yinbo Yu, Ran Wang, Daoqiang Zhang, Qi Zhu*

The article proposes a spatio-temporal hypergraph attention network framework for brain network analysis.

IEEE Transactions on Image Processing, 2026.

[PDF] [Code] [DOI]

Framework figure

Spatio-Temporal Evolutionary Graph Learning for Brain Network Analysis using Medical Imaging

Shengrong Li, Qi Zhu*, Chunwei Tian, Li Zhang, Bo Shen, Chuhang Zheng, Daoqiang Zhang, Wei Shao

This work proposes a topological evolution graph learning model to capture disease-related spatio temporal topological features in DFBNs.

IEEE Transactions on Image Processing, 2025.

[PDF] [Code] [DOI]

Framework figure

Interpretable Dynamic Brain Network Analysis with Functional and Structural Priors

Shengrong Li, Qi Zhu*, Chunwei Tian, Wei Shao, Daoqiang Zhang

In this paper, an interpretable spatio-temporal tensor graph convolutional network is proposed for DFBN analysis.

IEEE Transactions on Medical Imaging, 2025.

[PDF] [Code] [DOI]

Framework figure

Spatio-Temporal Graph Hubness Propagation Model for Dynamic Brain Network Classification

Qi Zhu, Shengrong Li, Xiangshui Meng, Qiang Xu, Zhiqiang Zhang, Wei Shao, Daoqiang Zhang

In this paper, optimal transport (OT) theory is introduced to capture the topology evolution of dynamic brain networks, and a multi-channel spatio-temporal graph convolutional network is developed to collaboratively extract temporal and spatial features from the evolution networks.

IEEE Transactions on Medical Imaging, 2024.

[PDF] [Code] [DOI]

Publications in this direction

[1]

Spatio-Temporal Hypergraph Attention Networks for Brain Disease Analysis

Chaojun Li, Peiliang Gong, Shengrong Li, Chunwei Tian, Yinbo Yu, Ran Wang, Daoqiang Zhang, Qi Zhu*

IEEE Transactions on Image Processing, 2026.

[PDF] [Code] [DOI]

[2]

Adjacent-aware Modality Recovery based on Incomplete Multi-Modal Brain Disease Diagnosis

Jinrong Cui, Weihao Ye, Shengrong Li, Jie Wen, Qi Zhu*

IEEE Transactions on Medical Imaging, 2026.

[PDF] [Code] [DOI]

[3]

Dual-contrastive modality recovery for incomplete multi-modal brain disease diagnosis

Jinrong Cui, Weihao Ye, Jie Wen, Qi Zhu*

Medical Image Analysis, 2026.

[PDF] [Code] [DOI]

[4]

Prototypical Representation Learning for Multi-Site Domain Generalization in Schizophrenia Diagnosis

Yixin Ji, Vince D Calhoun, Jin Zhang, Qi Zhu, Shengrong Li, Daniel H Mathalon, Si Yong Yeo, Daoqiang Zhang, Shile Qi

IEEE Transactions on Biomedical Engineering, 2026.

[PDF] [Code] [DOI]

[5]

A Unified Graph Domain Adaptation Framework for Cross-Site Brain Network Analysis

Lin Zhao, Cheng Ding, Shengrong Li, Chunwei Tian, Chao Huang, Donghai Guan, Daoqiang Zhang, Qi Zhu*

IEEE Transactions on Medical Imaging, 2026.

[PDF] [Code] [DOI]

[6]

Spatio-Temporal Evolutionary Graph Learning for Brain Network Analysis using Medical Imaging

Shengrong Li, Qi Zhu*, Chunwei Tian, Li Zhang, Bo Shen, Chuhang Zheng, Daoqiang Zhang, Wei Shao

IEEE Transactions on Image Processing, 2025.

[PDF] [Code] [DOI]

[7]

Interpretable Dynamic Brain Network Analysis with Functional and Structural Priors

Shengrong Li, Qi Zhu*, Chunwei Tian, Wei Shao, Daoqiang Zhang

IEEE Transactions on Medical Imaging, 2025.

[PDF] [Code] [DOI]

[8]

Enhancing Neurodegenerative Disease Diagnosis through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network

Ning Yuan, Donghai Guan, Shengrong Li, Li Zhang, Qi Zhu*

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2025.

[PDF] [Code] [DOI]

[9]

Multi-Modal Brain Network Fusion for Intelligent Diagnostic Devices

Shengrong Li, Qi Zhu*, Liang Sun, Kai Ma, Yixin Ji, Shile Qi, Daoqiang Zhang

IEEE Transactions on Consumer Electronics, 2025.

[PDF] [Code] [DOI]

[10]

Long-Interval Spatio-Temporal Graph Convolution for Brain Disease Diagnosis

Shengrong Li, Qi Zhu*, Donghai Guan, Bo Shen, Li Zhang, Yixin Ji, Shile Qi, Daoqiang Zhang

IEEE Transactions on Instrumentation and Measurement, 2025.

[PDF] [Code] [DOI]

[11]

Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis

Chaojun Li, Kai Ma, Shengrong Li, Xiangshui Meng, Ran Wang, Daoqiang Zhang, Qi Zhu*

NeuroImage, 2025.

[PDF] [Code] [DOI]

[12]

NeuroH-TGL: Neuro-Heterogeneity Guided Temporal Graph Learning Strategy for Brain Disease Diagnosis

Shengrong Li, Qi Zhu*, Chunwei Tian, Xinyang Zhang, Wei Shao, Jie Wen*, Daoqiang Zhang

Advances in Neural Information Processing Systems (NeurIPS), 2025.

[PDF] [Code] [DOI]

[13]

Spatio-Temporal Graph Hubness Propagation Model for Dynamic Brain Network Classification

Qi Zhu, Shengrong Li, Xiangshui Meng, Qiang Xu, Zhiqiang Zhang, Wei Shao, Daoqiang Zhang

IEEE Transactions on Medical Imaging, 2024.

[PDF] [Code] [DOI]

[14]

Ordinal Pattern Tree: A New Representation Method for Brain Network Analysis

Kai Ma, Xuyun Wen, Qi Zhu, Daoqiang Zhang

IEEE Transactions on Medical Imaging, 2024.

[PDF] [Code] [DOI]

[15]

MSTGC: Multi-Channel Spatio-Temporal Graph Convolution Network for Multi-Modal Brain Networks Fusion

Ruting Xu, Qi Zhu*, Shengrong Li, Zhenghua Hou, Wei Shao, Daoqiang Zhang

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023.

[PDF] [Code] [DOI]

[16]

Deep Multi-Modal Discriminative and Interpretability Network for Alzheimer's Disease Diagnosis

Qi Zhu, Bingliang Xu, Jiashuang Huang, Heyang Wang, Ruting Xu, Wei Shao, Daoqiang Zhang

IEEE Transactions on Medical Imaging, 2023.

[PDF] [Code] [DOI]

[17]

Multi-Modal Non-Euclidean Brain Network Analysis with Community Detection and Convolutional Autoencoder

Qi Zhu, Jing Yang, Shuihua Wang, Daoqiang Zhang, Zheng Zhang

IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.

[PDF] [Code] [DOI]

2. Brain-Computer Interfaces（脑机接口）
Framework figure

Heterogeneous Modality Dynamic Trustworthy Fusion Network for Cross-Subject Sleep Stage Classification

Kun Wang, Qi Zhu*, Junyong Zhao, Chuhang Zheng, Wei Shao, Daoqiang Zhang*

The paper proposes a Heterogeneous Modality Dynamic Trustworthy Fusion Network (HMDT-Net) for cross-subject sleep stage classification.

IEEE Transactions on Emerging Topics in Computational Intelligence, 2026.

[PDF] [Code] [DOI]

Framework figure

Disentangled Representation Learning for Robust Brainprint Recognition

Chuhang Zheng, Qi Zhu*, Lunke Fei, Shengrong Li, Xiangping Bryce Zhai, David Zhang, Daoqiang Zhang

This paper proposes a disentangled representation learning based identity recognition framework, which disentangles the EEG signal into intrinsic identity-related information and biased identity-invariant information, thus enhancing the performance of EEG biometrics.

IEEE Transactions on Information Forensics and Security, 2025.

[PDF] [Code] [DOI]

Framework figure

Multi-Modal Cross-Subject Emotion Feature Alignment and Recognition with EEG and Eye Movements

Qi Zhu, Ting Zhu, Lunke Fei, Chuhang Zheng, Wei Shao, David Zhang, Daoqiang Zhang

In this paper, a cross-subject multi-modal emotion recognition framework is proposed. The architecture jointly learns subject-independent representations and common features shared between EEG and eye movements.

IEEE Transactions on Affective Computing, 2025.

[PDF] [Code] [DOI]

Framework figure

HeLo: Heterogeneous Multi-Modal Fusion with Label correlation for Emotion Distribution Learning

Chuhang Zheng, Chunwei Tian, Wen Jie, Daoqiang Zhang, Qi Zhu*

In this paper, a multi-modal emotion distribution learning framework is proposed, aiming to fully explore the heterogeneity and complementary information in multi-modal emotional data, as well as the label correlation within mixed basic emotions.

ACM International Conference on Multimedia (ACM MM), 2025.

[PDF] [Code] [DOI]

Publications in this direction

[1]

Heterogeneous Modality Dynamic Trustworthy Fusion Network for Cross-Subject Sleep Stage Classification

Kun Wang, Qi Zhu*, Junyong Zhao, Chuhang Zheng, Wei Shao, Daoqiang Zhang*

IEEE Transactions on Emerging Topics in Computational Intelligence, 2026.

[PDF] [Code] [DOI]

[2]

Hash Prototype Personalized Federated Learning for Multi-Site Brain Network Analysis

Kun Wang, Qi Zhu*, Bo Qian, Mingming Wang, Liying Zhang, Shengrong Li, Daoqiang Zhang*

IEEE Transactions on Cognitive and Developmental Systems, 2026.

[PDF] [Code] [DOI]

[3]

FSDBN: Foreground-Aware EEG-Visual Alignment via Dynamic Brain Networks

Yiheng Liu, Chuhang Zheng, Peiliang Gong, Jingtao Liu, Daoqiang Zhang, Qi Zhu*

arXiv preprint arXiv:2607.18344, 2026. (Accepted by ACM MM 2026)

[PDF] [Code] [DOI]

[4]

ViEEG: Hierarchical Visual Neural Representation for EEG Brain Decoding

Minxu Liu, Donghai Guan*, Chuhang Zheng, Chunwei Tian, Jie Wen, Qi Zhu

arXiv preprint arXiv:2505.12408, 2026. (Accepted by NeurIPS 2026)

[PDF] [Code] [DOI]

[5]

Disentangled Representation Learning for Robust Brainprint Recognition

Chuhang Zheng, Qi Zhu*, Lunke Fei, Shengrong Li, Xiangping Bryce Zhai, David Zhang, Daoqiang Zhang

IEEE Transactions on Information Forensics and Security, 2025.

[PDF] [Code] [DOI]

[6]

Multi-Modal Cross-Subject Emotion Feature Alignment and Recognition with EEG and Eye Movements

Qi Zhu, Ting Zhu, Lunke Fei, Chuhang Zheng, Wei Shao, David Zhang, Daoqiang Zhang

IEEE Transactions on Affective Computing, 2025.

[PDF] [Code] [DOI]

[7]

Multi-Modal Discriminative Network for Emotion Recognition across Individuals

Minxu Liu, Donghai Guan, Chuhang Zheng, Qi Zhu*

IEEE Transactions on Cognitive and Developmental Systems, 2025.

[PDF] [Code] [DOI]

[8]

HeLo: Heterogeneous Multi-Modal Fusion with Label correlation for Emotion Distribution Learning

Chuhang Zheng, Chunwei Tian, Wen Jie, Daoqiang Zhang, Qi Zhu*

ACM International Conference on Multimedia (ACM MM), 2025.

[PDF] [Code] [DOI]

[9]

Dynamic Confidence-Aware Multi-Modal Emotion Recognition

Qi Zhu, Chuhang Zheng, Zheng Zhang, Wei Shao, Daoqiang Zhang

IEEE Transactions on Affective Computing, 2024.

[PDF] [Code] [DOI]

3. AI Interdisciplinary Applications（人工智能交叉应用）
Framework figure

Learning to Estimate 3D Hand Pose from Depth Image

Lunke Fei, Xin Wang, Qi Zhu, Shuping Zhao, Jie Wen, Jian Zhu, Xiaomin Hu

This paper proposes an attention-based graph convolutional network (AttGCN) for 3D hand pose estimation, learning fine-grained hand-joint features in a coarse-to-fine manner.

IEEE Transactions on Multimedia, 2026.

[PDF] [Code] [DOI]

Framework figure

PalmMamba: Palm Intrinsic Features Learning Selective State Space Model for Palmprint Image Denoising

Zhu Wang, Lunke Fei, Shuping Zhao, Bob Zhang, Qi Zhu, Imad Rida

This paper proposes a palm intrinsic feature learning selective state space model for palmprint image denoising, integrating shallow feature representation, noise-insensitive palmprint-specific feature learning, and sharp palmprint image restoration in a unified framework.

IEEE Transactions on Multimedia, 2025.

[PDF] [Code] [DOI]

Framework figure

Contactless Palmprint Image Recognition across Smartphones with Self-paced CycleGAN

Qi Zhu, Guangnan Xin, Lunke Fei, Dong Liang, Zheng Zhang, Daoqiang Zhang, David Zhang

This work proposes a self-paced CycleGAN with self-attention modules, which simultaneously synthesizes missing data and mitigates the impact of different imaging devices.

IEEE Transactions on Information Forensics and Security, 2023.

[PDF] [Code] [DOI]

Publications in this direction

[1]

Learning to Estimate 3D Hand Pose from Depth Image

Lunke Fei, Xin Wang, Qi Zhu, Shuping Zhao, Jie Wen, Jian Zhu, Xiaomin Hu

IEEE Transactions on Multimedia, 2026.

[PDF] [Code] [DOI]

[2]

Learning Multilayer Feature Projection for Homogeneous and Heterogeneous Palmprint Recognition

Lunke Fei, Kaiting Huang, Shuping Zhao, Qi Zhu, Bob Zhang, Wei Jia

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2026.

[PDF] [Code] [DOI]

[3]

AdaptPFL: Unlocking Cross-Device Palmprint Recognition via Adaptive Personalized Federated Learning with Feature Decoupling

Zirui Zhang, Donghai Guan, Cetin Kaya Koc, Qi Zhu*

IJCAI, 2025.

[PDF] [Code] [DOI]

[4]

Deep Multi-View Contrastive Clustering via Graph Structure Awareness

Lunke Fei, Junlin He, Qi Zhu, Shuping Zhao, Jie Wen, Yong Xu

IEEE Transactions on Image Processing, 2025.

[PDF] [Code] [DOI]

[5]

PalmMamba: Palm Intrinsic Features Learning Selective State Space Model for Palmprint Image Denoising

Zhu Wang, Lunke Fei, Shuping Zhao, Bob Zhang, Qi Zhu, Imad Rida

IEEE Transactions on Multimedia, 2025.

[PDF] [Code] [DOI]

[6]

A Cluster Tree Network for Image Super-Resolution

Qi Zhang, Weiqiang Xin, Shuai Wu, Qi Zhu, Qiya Song, Shichao Zhang

IEEE Transactions on Consumer Electronics, 2025.

[PDF] [Code] [DOI]

[7]

Semantic decomposition and enhancement hashing for deep cross-modal retrieval

Lunke Fei, Zhihao He, Wai Keung Wong, Qi Zhu, Shuping Zhao, Jie Wen

Pattern Recognition, 2025.

[PDF] [Code] [DOI]

[8]

Multi-instance Multi-task Learning for Joint Clinical Outcome and Genomic Profile Predictions from the Histopathological Images

Wei Shao, Hang Shi, Jianxin Liu, Yingli Zuo, Liang Sun, TianSong Xia, Wanyuan Chen, Peng Wan, JianPeng Sheng, Qi Zhu, Daoqiang Zhang

IEEE Transactions on Medical Imaging, 2024.

[PDF] [Code] [DOI]

[9]

Dense Hybrid Attention Network for Palmprint Image Super-Resolution

Yao Wang, Lunke Fei, Shuping Zhao, Qi Zhu, Jie Wen, Wei Jia, Imad Rida

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024.

[PDF] [Code] [DOI]

[10]

Multi-Spectral Palmprints Joint Attack and Defense with Adversarial Examples Learning

Qi Zhu, Yuze Zhou, Lunke Fei, Daoqiang Zhang, David Zhang

IEEE Transactions on Information Forensics and Security, 2023.

[PDF] [Code] [DOI]

[11]

Characterizing the Survival-Associated Interactions between Tumor-infiltrating Lymphocytes and Tumors from Pathological Images and Multi-omics Data

Wei Shao, Yingli Zuo, YangYang Shi, Yawen Wu, Jiao Tang, Junyong Zhao, Liang Sun, Zixiao Lu, Jianpeng Sheng*, Qi Zhu*, Daoqiang Zhang*

IEEE Transactions on Medical Imaging, 2023.

[PDF] [Code] [DOI]

[12]

Contactless Palmprint Image Recognition across Smartphones with Self-paced CycleGAN

Qi Zhu, Guangnan Xin, Lunke Fei, Dong Liang, Zheng Zhang, Daoqiang Zhang, David Zhang

IEEE Transactions on Information Forensics and Security, 2023.

[PDF] [Code] [DOI]

[13]

FAM3L: Feature-Aware Multi-modal Metric Learning for Integrative Survival Analysis of Human Cancers

Wei Shao, Jianxin Liu, Yingli Zuo, Shile Qi, Honghai Hong, Jianpeng Sheng*, Qi Zhu*, Daoqiang Zhang*

IEEE Transactions on Medical Imaging, 2023.

[PDF] [Code] [DOI]

[14]

Semi-Supervised Multi-View Fusion for Identifying CAP and COVID-19 with Unlabeled CT Images

Qi Zhu, Yuze Zhou, Yuan Yao, Liang Sun, Feng Shi, Wei Shao, Daoqiang Zhang, Dinggang Shen

IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.

[PDF] [Code] [DOI]

[15]

Selective oxidative protection leads to tissue topological changes orchestrated by macrophage during ulcerative colitis

Jianpeng Sheng, Juan Du, Junlei Zhang, Lin Wang, Xun Wang, Yaxing Zhao, Jiaoying Lu, Tingmin Fan, Meng Niu, Jie Zhang, Fei Cheng, Jun Li, Qi Zhu, Daoqiang Zhang, Hao Pei, Jing Zhang, He Huang, Xiaocang Cao, Xinjuan Liu, Wei Shao

Nature Communications, 2023.

[PDF] [Code] [DOI]

[16]

Self-Supervised Federated Adaptation for Multi-Site Brain Disease Diagnosis

Qiming Yang, Qi Zhu*, Mingming Wang, Wei Shao*, Zheng Zhang, Daoqiang Zhang

IEEE Transactions on Big Data, 2023.

[PDF] [Code] [DOI]

[17]

Multi-Discriminator Active Adversarial Network for Multi-Center Brain Disease Diagnosis

Qi Zhu, Qiming Yang, Mingming Wang, Xiangyu Xu, Yuwu Lu, Wei Shao, Daoqiang Zhang

IEEE Transactions on Big Data, 2023.

[PDF] [Code] [DOI]

Honors & Awards [Top]

Selected Student Awards (本组学生所获荣誉)

Professionals [Top]

Editorial Boards

Professional Societies & Committees

Conference Roles

Research Fund [Top]
Resources [Top]

Copyright © Qi Zhu