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。入选2023年江苏省“双创计划”科技副总计划人才。江苏省科技镇长团第16批数字经济产业团团员。2009年9月至2013年6月在复旦大学计算机科学与技术学院攻读计算机软件与理论专业博士学历，获理学博士学位。2014年1月进入江苏大学计算机科学与通信工程学院工作至今。现为中国人工智能学会会员、中国图象图形学会会员等。目前主要从事人工智能、计算机视觉、机器学习等方面的研究与教学工作，参与和主持过国家自然科学基金、中国博士后基金等5项。已发表IEEE Transactions、Elsevier等SCI/EI检索论文50余篇，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10多件，转让3件。

2013.06，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。危教授硕士、博士、博士后阶段分别师从怀进鹏院士（教育部部长）、何新贵院士、潘云鹤院士

2018.06，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

2016.08，美国Temple大学电子信息系访问学者，合作导师：Haibin Ling（现纽约州立大学教授），IEEE Fellow

2014.01-至今，江苏大学计算机科学与通信工程学院，副教授

教研成果

【近几年主要学术论文】：

【2024年】

[1] Xuecheng Hua, Ke Cheng, Hu Lu, 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] Yunyao Cai, Hu Lu, 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. doi: 10.1109/JBHI.2024.3486966. (中科院1区)

[3] 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)

[4] 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)

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

[6] 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*（通讯）. 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*（通讯）, 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*（通讯）, 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*（通讯）, 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*（通讯）, 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*（通讯）, 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*（通讯）, 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*（通讯）. Click-cut: A framework for interactive object selection [J]. Multimedia Tools and Applications. March 30, 2021. (SCI检索，Impact factor=2.757)

【指导研究生获奖】

[1] 全国数学建模一等奖： 2020年中国研究生创新实践大赛 “华为杯”第十七届中国研究生数学建模竞赛，全国一等奖 研究生：陈超

[2] 江苏省“互联网+”与智能农业一等奖： 2019年 “互联网+”与智能农业研究生学术创新论坛，一等奖，最佳论文奖 研究生：刘赛雄

【致新研究生】

本实验室围绕着人工智能、机器学习、计算机视觉、机器视觉等领域展开基础应用研究。热忱欢迎对此感一点兴趣、且想发SCI论文的同学加入。不论你本科毕业于何处，只要在研一、研二期间能做到两条：（1）早上9：00-9：30进入实验室；（2）完成两个小的研究内容。我们都可以合作，共同前进，交出一份合格的硕士毕业大论文（外审成绩80分以上）顺利毕业是我们共同的目标！

【指导本科生获奖】

[1] 2024年指导3组学生参加人工智能大赛，3组全获省一，进入国赛获国二、国三各一组

【致本科生-2025年人工智能算法竞赛参赛招募令】

为学院参与各类人工智能竞赛储备人才！本实验室也欢迎有理想、能坚持的本科生进来参加科研训练和项目实践（三天打鱼、两天晒网的同学请绕过），为后续参加人工智能类竞赛打好基础。

欢迎有兴趣的同学发我电子邮箱-luhu@ujs.edu.cn、或微信-18952881128。