职务职称：

副教授、硕导

所属系部：

计算机科学系

研究方向：

人工智能、计算机视觉

联系电话：

18952881128（微信）

电子邮箱：

luhu@ujs.edu.cn

  陆虎，江苏无锡人，副教授，硕士生导师。复旦大学计算机科学与技术学院计算机软件与理论专业理学博士毕业。主要从事人工智能、计算机视觉、机器视觉等领域的研究与产业化。现为中国人工智能学会会员、中国图象图形学会会员等。参与和承担过国家自然科学基金、中国博士后基金等多项。已发表IEEE Transactions、Elsevier等SCI/EI检索论文60多篇，其中包括人工智能研究领域顶会论文AAAI、ICCV和顶刊论文TAI、PR等多篇。已申请国家发明专利、软件著作权20多件，转让10余件。

2013年12月-至今，江苏大学计算机科学与通信工程学院工作

2014-2018，复旦大学软件学院，软件工程博士后流动站出站，合作导师：牛军钰教授、危辉教授

2009-2013，复旦大学计算机科学技术学院，计算机软件与理论专业博士毕业，导师：危辉教授(危辉教授硕士、博士、博士后阶段分别师从怀进鹏院士、何新贵院士、潘云鹤院士)

2016，美国Temple大学电子信息系访问学者，合作导师：凌海斌(现西湖大学讲席教授，IEEE Fellow)

2025，镇江市“金山英才.专项”计划

2023-2024，江苏省科技镇长团第16批数字经济产业团团员

2023，江苏省“双创计划”科技副总计划

教研成果

【近几年主要学术论文】：

【2026年】

[1] Dongqi Han, Yao Zhang, Fanghao Li, Shengli Wu, Hu Lu*(通信作者). Complex Query Answering on Knowledge Graphs with Griffin and Polarity-Weighted Message Passing, Knowledge and Information Systems, Accepted, 2026.  (SCI检索, CCF-B类)

【2025年】

[1] Hu Lu, Haotian Hong, Fuhao Shi, Shengli Wu, Lixin Duan. Deep contrastive graph clustering with information preservation, Pattern Recognition, Volume 172, Part C,2026,112575, https://doi.org/10.1016/j.patcog.2025.112575. 2025.  (SCI检索)

[2] Hu Lu et,al, Transformer-based Decoupled Modality Feature Learning for Visible-Infrared Person Re-Identification. IEEE MultiMedia, 10.1109/MMUL.2026.3652838, 2025. (SCI检索)

[3] Hu Lu, Yanyan Zhao, Guo Yang, Shengli Wu. DSGNet: A Lightweight Network Integrating Depthwise Separable and Ghost Convolutions for Real-Time Surface Defect Segmentation. Expert Systems. https://doi.org/10.1111/exsy.70187, 2025. (SCI检索)

[4] Fuhao Shi, Hu Lu*(通信作者). Enhancing multi-view deep image clustering via contrastive learning for global and local consistency. Pattern Analysis and Applications 28 (4), 165, 2025 (SCI检索)

[5] XueCheng Hua, Ke Cheng, Gege Zhu,  Hu Lu*(通信作者),  YuanQuan Wang,  ShiTong Wang,  Local-Aware Residual Attention Vision Transformer for Visible-Infrared Person Re-Identification.   ACM Transactions on Multimedia Computing, Communications, and Applications.  21(5) 1-24, 2025.  (SCI检索)

[6] Fuhao Shi, Shaohua Wan, Shengli Wu, Hui Wei, Hu Lu* (通信作者). Deep contrastive coordinated multi-view consistency clustering.  Machine Learning, doi : 10.1007/s10994-025-06735-y.  (2025) 114:81  (SCI检索)

[7] Yunyao Cai, Hu Lu* (通信作者), Shengli Wu, Stefano Berretti, Shaohua Wan. DT-VNet: Deep Transformer-based VNet Framework for 3D Prostate MRI Segmentation.  IEEE Journal of Biomedical and Health Informatics. 2025, doi: 10.1109/JBHI.2024.3486966. (SCI检索)

[8] Yuxin Li, Hu Lu*(通信作者), Tingting Qin, Juanjuan Tu, Shengli Wu. CM-DASN: Visible-Infrared Cross-Modality Person Re-Identification via Dynamic Attention Selection Network.  Multimedia Systems,  doi: 10.1007/s00530-025-01724-6, 2025. (SCI检索)

【2024年】

[1] Xuecheng Hua, Ke Cheng, Hu Lu(通信作者), Juanjuan Tu, Yuanquan Wang, Shitong Wang. MSCMNet: Multi-scale Semantic Correlation Mining for Visible-Infrared Person Re-Identification, Pattern Recognition, 2024,111090, doi.org/10.1016/j.patcog.2024.111090. (中科院1区)

[2] Yuhao Wang, Xuehu Liu, Pingping Zhang, Hu Lu, Zhengzheng Tu, Huchuan Lu, TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation. Association for the Advancement of Artificial Intelligence, AAAI-2024, 20-27 February，2024. (CCF-A类)

[3] Hu Lu, TingTing Jin，Hui Wei, Michele Nappi，Hu Li, ShaoHua Wan，Soft-orthogonal Constrained Dual-stream Encoder with Self-supervised Clustering Network for Brain Functional Connectivity Data. Expert Systems With Applications, 244, 122898, （2024）. (中科院1区)

[4] Ke Cheng, Qikai Geng, Shucheng Huang, Juanjuan Tu, Hu Lu*（通信作者）: Learning shared features from specific and ambiguous descriptions for text-based person search. Multim. Syst. 30(2): 94 (2024). (Impact factor=3.9)

[5] Hu Lu, Haotian Hong, Xia Geng: Deep Self-Supervised Attributed Graph Clustering for Social Network Analysis. Neural Process. Lett. 56(2): 130 (2024). (Impact factor=3.1)

【2023年】

[1] Hu, Lu, Xuezhang Zou, Pingping Zhang, Learning Progressive Modality-shared Transformers for Effective Visible-Infrared Person Re-identification. Association for the Advancement of Artificial Intelligence 2023, AAAI-2023. (CCF-A类)

[2] Ziqiang He, Shaohua Wan, Marco Zappatore, Hu Lu*（通信作者）. A Similarity Matrix Low-Rank Approximation and Inconsistency Separation Fusion Approach for Multi-View Clustering. IEEE Transactions on Artificial Intelligence. TAI. 2023, DOI: 10.1109/TAI.2023.3271964.

[3] Yirui Wu, Lilai Zhang, Zonghua Gu, Hu Lu, Shaohua Wan. Edge-AI-Driven Framework with Efficient Mobile Network Design for Facial Expression Recognition. ACM Transactions on Embedded Computing Systems. 2023, DOI:10.1145/3587038.

[4] Chao Chen, Hu Lu*（通信作者）, Haotian Hong, Hai Wang, Shaohua Wan. Deep Graph Attention Convolution Autoencoder Clustering for Social Network Connection Analysis. TCE, IEEE Transactions on Consumer Electronics. 2023.

【2022年】

[1] Li, H., Wu Y., Hu, H., Lu, H., Lai, Y., Wan, S., Learning Group-Disentangled Representation for Interpretable Thoracic Pathologic Prediction. International Conference on Bioinformatics & Biomedicine 2022, BIBM-2022. (CCF-B类)

[2] Ding, S., Wang, H., Lu, H., Nappi, M., & Wan, S. (2022). Two path gland segmentation algorithm of colon pathological image based on local semantic guidance. IEEE journal of biomedical and health informatics, (SCI检索，Impact factor: 7.021)

[3] Chao Chen, Hu Lu*（通信作者）, Hui Wei, Xia Geng. Deep Subspace Image Clustering Network with Selfexpression and Self-supervision [J]. Applied Intelligence. accepted, 2022, (SCI检索，Impact factor=5.086)

[4] Hu Lu, Chao Chen, Hui Wei, Zhongchen Ma, Ke Jiang, Yingquan Wang. Improved Deep Convolutional Embedded Clustering with Re-selectable Sample Training [J]. Pattern Recognition. Volume 127, 2022, doi : 10.1016/j.patcog.2022.108611. (SCI检索，Impact factor=7.74)[source code]

[5] Hu Lu*（通信作者）, Tingting Jin. Dual-Stream Encoder Neural Networks with Spectral Constraint for Clustering Functional Brain Connectivity Data [J]. Neural Computing and Applications. 2022, doi : 10.1007/s00521-022-07122-7. (SCI检索，Impact factor=5.606)[source code]

[6] Yingquan Wang, Ke Jiang, Hu Lu*（通信作者）, Ziheng Xu, Gaojian Li, Chao Chen, Xia Geng. Encoder-Decoder Assisted Image Generation for Person re-identification[J]. Multimedia Tools and Applications. 2022, doi : 10.1007/s11042-022-11907-2. (SCI检索，Impact factor=2.757)

【2021年】

[1] Yingquan Wang, Pingping Zhang, Shang Gao, Xia Geng, Hu Lu*（通信作者）, Dong Wang. Pyramid Spatial-Temporal Aggregation for Video-based Person Re-Identification. Proceedings of the IEEE International Conference on Computer Vision, v 2021-October, p12026-12035, Proceedings - 2021 International Conference on Computer Vision,  ICCV 2021. (CCF-A类)

[2] Hu Lu*（通信作者）, Saixiong Liu, Hui Wei, Chao Chen, Xia Geng, Deep multi-kernel auto-encoder network for clustering brain functional connectivity data. Neural Networks. Volume 135, 2021, pp 148-157. DOI: 10.1016/j.neunet.2020.12.005. (SCI检索，Impact factor=8.05)

[3] Thomas Martial Epalle*, Yuqing Song, Zhe Liu, Hu Lu. Multi-atlas Classification of Autism Spectrum Disorder with Hinge Loss Trained Deep Architectures: ABIDE I Results [J]. Applied Soft Computing. March 29, 2021. (SCI检索，Impact factor=6.725)

[4] Hu Lu*（通信作者）. Click-cut: A framework for interactive object selection [J]. Multimedia Tools and Applications. March 30, 2021. (SCI检索，Impact factor=2.757)

【欢迎新研究生的加入】

本实验室围绕着人工智能、机器学习、计算机视觉、机器视觉、大语言模型LLM等领域开展基础研究、应用项目开发。欢迎对此感兴趣的同学加入。

全日制硕士研究内容围绕着（1）基于深度学习、大模型的行人感知检测及其在空-地智能方向的应用；（2）基于深度学习、大模型的机器学习方法研究及其应用。

非全日制硕士目前承担的课题有（1）基于大型语言模型的知识库问答系统开发； （2）典型中间产品作业模型标准化设计；（3）典型中间产品标准工序设计可视化模块设计；（4）标准工序系统与工艺设计平台接口设计。

【欢迎本科生的加入】

本实验室也欢迎有科研想法、能坚持的本科生来参加科学研究和项目训练（做事三分钟热度的同学请绕过），也可一起合作后续参加各项人工智能类竞赛及挑战赛。

欢迎有兴趣的同学可发邮箱-luhu@ujs.edu.cn、或微信联系-18952881128