卢 宏涛 教授
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办公室电话：+86-21-3420-4879
办公地点：SEIEE-3-425
电子邮件：lu-ht@cs.sjtu.edu.cn
实验室： 智能计算与智能系统重点实验室、 上海市教委智能交互与认知工程重点实验室


研究兴趣
教育背景
工作经验
教授课程
论文发表
项目资助
获奖信息
学术服务




卢宏涛，上海交通大学计算机系长聘教授，博士生导师。研究兴趣为机器学习、深度学习、计算机视觉、模式识别。在国际知名学术期刊和国际顶级学术会议上发表论文100余篇，其中63篇被SCI收录，SCI他引超过1360次；GoogleScholar引用超过4000次，H-index 37。先后主持国家863、国家自然科学基金、教育部博士点基金、上海市科委和上海市曙光计划等10多项项目。连续入选2014-2018年Elsevier计算机科学中国高被引****榜单。入选2005年度教育部新世纪优秀人才计划，2003年获上海市曙光****称号，2010年获上海市自然科学二等奖，2015年获河南省科技进步二等奖。
已指导研究生13人获得博士学位，58人获得硕士学位，35人获得在职专业硕士学位，毕业的研究生中已有不少成为985、211等大学的教授或院长。硕士生则主要供职于华为、BAT、Google、微软、Facebook等公司。现有在读博士研究生11人、硕士研究生8人，其中各类留学生5人。指导ACM班、IEEE班、计算机专业及其它相关专业本科毕业设计58人。他们中许多在Stanford、MIT、CMU等世界名校继续深造。

1993年9月－1997年1月，东南大学无线电工程系，获工学博士学位, 导师：何振亚教授
1987年9月－1990年7月，四川师范大学数学系，获理学硕士学位，导师：丁协平教授
1983年9月－1987年7月，四川师范大学数学系，获理学学士学位

2016年5月至今，上海交通大学计算机系，长聘教授
2001年5月 - 2016年5月，上海交通大学计算机系，教授
1999年1月 -2001年7月，上海交通大学计算机系，副教授
1997年2月 - 1999年1月，复旦大学计算机系，博士后
1990年7月 - 1993年8月，云南楚雄师范专科学校数学系，教师

短期访问：
2015年1月，西班牙巴斯克大学访问
2005年6月－2005年8月，香港城市大学，访问****
2005年3月－2005年4月，日本理化学研究所脑科学研究中心，访问****
2004年6月－2004年8月，日本理化学研究所（RIKEN）脑科学研究中心，访问****
2001年11月－2002年7月，香港理工大学计算学系，访问****
2001年2月－2001年5月，香港城市大学电子工程系，访问****

1.计算机科学导论（ACM班）
2.科研专题讨论（ACM班）
3.离散数学（本科）
4.人工智能（本科）
5.数字图像处理（本科、硕士、博士）
6.图像处理与机器视觉（研究生）

代表性论文（机器学习、计算机视觉）：

1. Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, Baining Guo.Learning Texture Transformer Network for Image Super-Resolution. CVPR 2020.(CCF A)
2. Yaoyi Li, Hongtao Lu.Natural Image Matting via Guided Contextual Attention. AAAI 2020. (CCF A)
3. Li Wang, Zechen Bai,Yonghua Zhang, Hongtao Lu. Show, Recall, and Tell: Image Captioning with RecallMechanism. AAAI 2020. (CCF A)
4. Yiru Zhao, Xu Shen,Zhongming Jin, Hongtao Lu, Xiansheng Hua. Attribute-Driven FeatureDisentangling and Temporal Aggregation for Video Person Re-Identification. CVPR2019. (CCF A)
5. Yu Qin, Jiajun Du,Yonghua Zhang, Hongtao Lu. Look Back and Predict Forward in Image Captioning. CVPR2019. (CCF A)
6. Yiru Zhao, ZhongmingJin, Guojun Qi, Hongtao Lu, Xuansheng Hua. An adversarial approach to hardtriplet generation. ECCV 2018. (CCF B)
7.Fei Jiang, Xiangyang Liu, Hongtao Lu,Ruiming Shen. Efficient Multi-dimensional Tensor Sparse Coding Using t-linearCombination. AAAI 2018. (CCF A)
8. Yiru Zhao, BingDeng, Jianqiang Huang, Hongtao Lu, Xiansheng Hua. Stylized AdversarialAutoEncoder for Image Generation. Proceedings of the 2017 ACM on MultimediaConference(MM ’17). ACM, Mountain View, California, USA,2017.10.23-10.27, 244-251. (CCF A)
9.Yiru Zhao, Chen Shen, Yao Liu, HongtaoLu, Xiansheng Hua. Spatio-Temporal AutoEncoder for Video Anomaly Detection.Proceedings of the 2017 ACM on Multimedia Conference(MM ’17). ACM,Mountain View, California, USA, 2017.10.23-10.27, 1933-1941. (CCF A)
10.Zihao Hu,Junxuan Chen, Hongtao Lu, Tongzhen Zhang. Bayesian Supervised Hashing. IEEEInternational Conference on Computer Vision and Pattern Recognition (CVPR 2017),pp. 4321-4328. (CCF A)
11. Qi Liu, Hongtao Lu.Natural supervised Hashing, IJCAI 2016 (Oral). (CCF A)
12.Junxuan Chen, Baigui Sun, Hao Li,Hongtao Lu, Xian-Sheng Hua. Deep CTR Prediction in Display Advertising. ACMMultimedia 2016 (oral). (CCF A)
13.Yiru Zhao, Yaoyi Li, Zhiwen Shao,Hongtao Lu. LSOD: Local Sparse Orthogonal Descriptor for Image Matching. ACMMultimedia, 2016. (CCF A)
14. Kang Zhao, Hongtao Lu.Locality Preserving Hashing. AAAI 2014. (CCF A)
15.KangZhao, Hongtao Lu. LocalityPreserving Discriminative Hashing. ACM Multimedia, 2014. (CCF A)
16. Zhenyong Fu, HongtaoLu, Horace Ip. Modalities Consensus for Multi-Modal Constraint Propagation. ACMMultemedia 2012, 773-776. (CCF A)
17. Zhenyong Fu, HoraceH.S. Ip, Hongtao Lu, and Zhiwu Lu. Multi-model Constraint Propagation for ImageClustering. ACM Multimedia 2011. CCF A, Long Paper, Oral.（Acce ptance rate for long paper 13%）
18.Zhenyong Fu, Horace H.S. Ip, HongtaoLu. Symmetric Graph Regularized Constraint Propagation. AAAI2011, pp.350-355,2011.CCF A.
19. Wei He, Takayoshi,Hongtao Lu, and Shihong Lao, “SURF tracking,” the twelfthInternational Conference on Computer Vision (ICCV2009, CCF A，acceptance rate 12%), Kyoto, Japan,Sep.29-Oct.2, 2009.
20. Qijun Zhao, David Zhang and Hongtao Lu, A direct evolutionary feature extractionalgorithm for classifying high dimensional data. AAAI’06, pp.561-566,2006. CCFA
21. Yaoyi Li, Hongtao Lu.On Multi-modal Fusion Learning in constraint propagation. Information Science,pp.204-217, 2018.
22.Shicong Liu, Junru Shao, Hongtao Lu.Generalized residual vector quantization and aggregating tree for large scalesearch. IEEE Transactions on Multimedia, VOL. 19, NO. 8, AUGUST 2017, pp.1785-1797.
23.Hongbin Yu, Hongtao Lu. Orthogonaloptimal reverse prediction for semi-supervised learning. Pattern recognition,60(2016) 908-920.
24. Hongtao Lu,ZhenyongFu, XinShu. Non-negative and sparse spectral clustering. PatternRecognition, Pattern Recognition, 47(2014)418-426.

其它论文（机器学习、计算机视觉）


期刊论文：
1. Yiru Zhao, Hongtao Lu. Neighbor similarity and soft-labeladaptation for unsupervised cross-dataset person re-identification.Neurocomputing, 2020.
2. Hongbin Yu, Hongtao Lu, Shuihua Wang, Kaijian Xia, Yizhang Jiang,Pengjiang Qian: A General Common Spatial Patterns for EEG Analysis WithApplications to Vigilance Detection. IEEE Access 7: 111102-111114 (2019)
3.QingGuan, Yunjun Wang, Jiajun Du, Yu Qin, Hongtao Lu, Jun Xiang, Fen Wang. Deeplearning based classification of ultrasound images for thyroid nodules: a largescale of pilot study. Annals of Translational Medicine, 2019;7(7):137.
4. Qing Guan, Xiaochun Wan, Hongtao Lu, Bo Ping, Duanshu Li, LiWang, Yunjun Wang, Jun Xiang. Deep convolutional neural network Inception-v3model for differential diagnosing of lymph node in cytological images: a pilotstudy. Ann Transl Med 2019 | http://dx.doi.org/10.21037/atm.2019.06.29.
5. Qing Guan, Yunjun Wang, Bo Ping, Duanshu Li, Jiajun Du, Yu Qin,Hongtao Lu, Xiaochun Wan, Jun Xiang. Deep convolutional neural network VGG-16model for differential diagnosing of papillary thyroid carcinomas incytological images: a pilot study. Journal of Cancer 2019, Vol. 10:4876.
6. Zhenyong Fu, Lu Zhiwu, Horace Ip, HongtaoLu, Wang Yunyun. Local similarity learning for pairwise constraint propagation.Multimedia tools and applications. 74(11): 3739-3758, 2015.
7.Yangcheng He, Hogntao Lu, Lei Huang, Saining Xie. Pairwise constrained conceptfactorization for data representation. Neural Networks 52(2014)1-17.
8. XianzhongLong, Hongtao Lu, Yong Peng, Wenbin Li. Graph regularized discriminativenon-negative matrix factorization for face recognition. Multimedia tools andapplications, (2014)72:2679-2699.
9. XinShu, Hongtao Lu. Linear discriminant analysis with spectral regularization.Applied intelligence, 2014.
10.Wei Huang, Hongtao Lu. Automatic defect classification of TFT-LCD panels withshape, histogram and color features. International Journal of Image andGraphics, Vol. 13, No. 3 (2013) **.
11.YangchengHe, Hongtao Lu, Saining Xie. Semi-supervised Non-negative Matrix Factorizationfor Image Clustering with Graph Laplacian. Multimedia Tools and Applications.2013, DOI：10.1007/s11042-013-1465.
12.Xianzhong Long, Hongtao Lu, Wenbin Li. Image classification based on nearestneighbor basis vectors. Multimedia Tools and Applications. 2012, DOI：10.1007/s11042-012-1289-4.
13.JingnanGu, Hongjun Liu, Hongtao Lu and Baoliang Lv. An integral Gaussian mixture modelto estimate vigilance level based on EEG Recordings. Neurocomputing 129(2014)107-113.
14.PanZhifang, Lu Hongtao, Cheng Qi. Activity of daily living and lesion positionamong multiple sclerosis patients by Bayes network. Neural RegenerationResearch, 8(14):1327-1336,2013. (SCI)
15. XinShu,Yao Gao,Hongtao Lu, Efficient linear discriminant analysis with localitypreserving for face recognition. Pattern Recognition, v 45, n 5, p 1892-1898,May 2012.
16.YuGang; Hu Zhiwei; Lu Hongtao. Robust object tracking with occlusion handle. Neuralcomputing&applications, vol. 20, no. 7, special issue, pages:1027-1034 DOI: 10.1007/s00521-010-0400-x, OCT 2011.
17.Zhang Tongzhen; Shen Ruimin; Lu Hongtao. Using Non-Negative Matrix Factorization to Cluster Learnersand Construct Learning Communities. Chinesejournal of electronics, vol. 20, no. 2, pp. 207-211, APR 2011.
18.Pan zhifang, Hu zhiwen, Lu Hongtao. Classification of alzheimer’s disease usinga novel PCA method based on matrix factorization. International Journal ofAdvancements in Computing Technology, v 3, n 10, p 283-290, November 2011.
19.Zhenyong Fu, Hongtao Lu, and Wenbin Li. Incremental Visual Objects Clusteringwith the Growing Vocabulary Tree. Multimedia and applications. DOI10.1007/s11042-010-0616-x, 2010.
20.Tian Ouyang, Hong-Tao Lu, Bao-Liang Lu, “Vigilance Analysis Based on EEGSignals: Seeking for Suitable Features,” Journal of Biological Systems, vol.18,2010.
21.Qijun Zhao, David Zhang, L. Zhang and Hongtao Lu ，“EvolutionaryDiscriminant Feature Extraction with Application to Face Recognition,” EURASIPJournal on Advances in Signal Processing, vol.2009, paper ID 465193.
22.Qijun Zhao, Hongtao Lu and David Zhang, “A fast evolutionary pursuit algorithmbased on linearly combining vectors,” Pattern recognition, 39(2006) 310-312.

会议论文：
1.YaoyiLi, Jianfu Zhang, Weijie Zhao, Weihao Jiang and Hongtao Lu. Inductive guidedfilter: real-time deep matting with weakly annotated masks on mobile devices.ICME 2020. (CCF B)
2.ChangLiu, Hongtao Lu. A highly efficient trainig-aware convolutional neuralnetwork compression paradigm. ICME Workshop, 2020.
3.WeihaoJiang, Zhaozhi Xie, Yaoyi Li, Chang Liu, Hongtao Lu. LRNNET: A light-weightednetwork with efficient reduced non-local operation for real-time semanticsegmentation. ICME Workshop, 2020.
4.MengZhou, Yaoyi Li, Hongtao Lu, CaiNengbin, ZhaoXuejun. Semi-Supervised Meta-Learningvia Self-Training. ISA 2020.
5.HaotianTang, Yiru Zhao, Hongtao Lu. Unsupervised Person Re-Identification withIterative Self-Supervised Domain Adaptation. CVPR Workshop, 2019.
6.UsmanAli, Bayram Bayramli and Hongtao Lu. TemporalContinuity Based Unsupervised Learning for Person Re-Identification. ICONIP2019.
7.ZhenruLi, Yaoyi Li, Hongtao Lu and Usman Ali. Improve Image Captioning byself-attention. ICONIP 2019.
8.YuQin, Jiajun Du, Xinyao Wang, Hongtao Lu. Recurrent Layer Aggregation usingLSTM. IJCNN, 2019.
9.JiajunDu, Yu Qin, Hongtao Lu, Network Search for Binary Networks. IJCNN, 2019.
10.BayramBayramli, Hongtao Lu. FH-GAN: Face Hallucination and Recognition usingGenerative Adversarial Networks. ICONIP 2019.
11.WenboLi, Hongtao Lu. Multi-level Collaborative Attention Network for Person Search.ACCV 2018.
12.KaichengTang, Xiaohua Shi, Hongtao Lu. Image recognition with deep learning for librarybook identification. 19^th Pacific-Rim Conference on Multimedia, PCM2018.
13. FeiJiang, Xiao-Yang Liu, Hongtao Lu, Ruimin Shen. Anisotropic total variationregularized low-rank tensor completion based on tensor nuclear norm for colorimage inpainting. ICASSP 2018. (CCF B)
14.Qite,Hongtao Lu，Huiyu Weng. Modeling Long Range Relations by Feature Translation.ICMV（2018 The 11th International Conference on Machine Vision）, 2018.
15.DeyiJi, Hongtao Lu, Tongzhen Zhang. End to end multi-scale convolutional neuralnetworks for crowd counting. ICMV（2018The 11th International Conference on Machine Vision）, 2018.
16.ZeChen, Hongtao Lu. Recurrent Spatiotemporal Feature Learning for ActionRecognition. 2018 the 4th International Conference on Robotics and ArtificialIntelligence - ICRAI 2018.
17.ShicongLiu, Hongtao Lu. Space shuttle model: a physics inspired method for learningquantizable deep representations. Proceedings of the IEEE InternationalConference on Multimedia and Expo (ICME) 2017, 10-14 July 2017, pp.121-126.(CCF B)
18.ShicongLiu, Hongtao Lu. Quantizable deep representation learning with gradientsnapping layer for large scale search. Proceedings of the IEEE InternationalConference on Multimedia and Expo (ICME) 2017, 10-14 July 2017, pp.1380-1385.(CCF B)
19.HualongHuang, Bo Huang, Hongtao Lu, and Huiyu Weng. Stereo Matching using ConditionalAdversarial Networks. International Conference on Neural Information ProcessingICONIP 2017, pp 124-132.
20.BoHuang, Hualong Huang, and Hongtao Lu. Convolutional Gated Recurrent UnitsFusion for Video Action Recognition. International Conference on NeuralInformation Processing ICONIP 2017, pp 114-123.
21.XiaohuaShi, Hongtao Lu, Guanbo Jia. Adaptive Overlapping Community Detection withBayesian NonNegative Matrix Factorization. International Conference on DatabaseSystems for Advnced Applications DASFAA, 2017, pp 339-353. (CCF B)
22.YurunShen, Hongtao Lu, Jie Jia. Classification of Motor Imagery EEG Signals withDeep Learning Models. International Conference on Intelligence Science and BigData Engineering, IScIDE 2017: pp 181-190.
23. JunxuanChen, Hongtao Lu. Online self-organizing hashing. ICME 2016. (CCF B)
24.ShicongLiu, Hongtao Lu. Generalized residual vector quantization for large scale data.ICME 2016. (Oral) (CCF B)
25.Yaoyi Li, Hongtao Lu. Adaptive Affinity Matrix for Unsupervised MetricLearning. ICME 2016. (Oral) (CCF B)
26.Mingxuan Di, Guang Yang, Qinchuang Zhang, Kang Fu, Hongtao Lu. Fast visualobject tracking using convolutional filters. ICONIP, 2016.
27.YangchengHe, Hongtao Lu, Baoliang Lu. Graph regularized non-negative local coordinatefactorization with pairwise constraints for image representation. ICME 2015.(CCF B)
28.LiWu, Kang Zhao, Hongtao Lu_, Zhen Wei, Baoliang Lu. Distance preserving marginalhashing for image retrieval. ICME 2015. (CCF B)
29.PanChen, Yangcheng He, Hongtao Lu. Constrained Non-negative matrix factorizationwith graph Laplacian. ICONIP 2015.
30.XiaohuaShi, Hongtao Lu, Yangcheng He, Shan He. Community detection with pairwiseconstrained symmetric non-negative matrix factorization. ASONAM’15 Proceedingsof the 2015 IEEE/ACM International Conference on Advances in Social NetworksAnalysis and Mining, pages 541-546, 2015.
31.XuejiaoBai, Xuan Luo, Shuo Li, Adaptive stereo matching by loop-erased random walk.ICIP 2014.
32.YuzhangYuan, Hongtao Lu. Multi-label linear discriminant analysis with LocalityConsistency. ICONIP, 2014.
33.DongXing, Xianzhong Wang, Hongtao Lu. Action Recognition Using Hybrid FeatureDescriptor and VLAD Video Encoding, ACCV Workshop 2014.
34.XianzhongWang, Hongtao Lu, Xianzhong Long. Action recognition with uncertain VLAD. 2014Seventh International Symposium on Computational Intelligence and Design,pp.185-188.
35.DengxiangLiu, Hongtao Lu. Layered Recommendation: a New Strategy for Movie Promotion.2014 7th International Congress on Image and Signal Processing (CISP 2014),2014.
36.ZhuoWang, Hongtao Lu. Online Recommender System Based on Social NetworkRegularization. ICONIP(1) 2014: 487-494.
37.SainingXie, Jiashi Feng, Shuicheng Yan, Hongtao Lu. Perception Preserving Projections.BMVC (Oral),2013.
38.ShaokunFeng, Hongtao Lu. Image classification based on weight adjustment beforefeature pooling. ICONIP, 2013, Part III, LNCS 8228, pp. 360–367, 2013.
39. KangZhao, Dengxiang Liu, Hongtao Lu. Local Linear Spectral Hashing, ICONIP 2013,Part III, LNCS 8228, pp. 283–290, 2013.
40.Xianzhong Long, Hongtao Lu, Yong Peng. Sparse Non-Negative Matrix Factorizationbased on Spatial Pyramid Matching for Face Recognition. 2013 Fifth InternationalConference on Intelligent Human-Machine Systems and Cybernetics.
41.YiDing, Hongtao Lu. Sparse Representations of Clustered Video Shots for ActionRecognition. IEEE 3rd International Conference on Computer Science and NetworkTechnology, 2013.
42.Lei Huang, Zhifang Pan, Hongtao Lu. Automated Diagnosis of Alzheimer’s Diseasewith Degenerate SVM-based Adaboost. 2013 Fifth International Conference onIntelligent Human-Machine Systems and Cybernetics.
43. SaningXie, Hongtao Lu and Yangcheng He. Multi-Task Co-clustering via NonnegativeMatrix Factorization. International Conference on Pattern Recognition(ICPR2012), accepted.
44.Lei Huang, Hongtao Lu, Wei Huang. Automated Defect Classification with SVM-basedAdaboost. International Conference on Computer and Information Science, SafetyEngineering (CAISSE2012). (Best paper award)
45.XianzhongLong, Hongtao Lu and Xin Shu. An Efficient Data Dimensionality Reduction Schemebased on SIFT for Face Recognition. 2012 International Conference on WebInformation Systems and Mining (WISM’12) and the 2012 International Conferenceon Artificial Intelligence and Computational Intelligence (AICI’12).WISM’12-AICI’12, accepted.
46.XinShu, Hongtao Lu. Neighborhood Structure Preserving Ridge Regression forDimensionality Reduction. Chinese Conference on Pattern Recognition (CCPR 2012)， accepted.
47.HongtaoLu, Xianzhong Long and Jingyuan Lv. A Fast Algorithm for Recovery of JointlySparse Vectors based on the Alternating Direction Methods. Journal of MachineLeaning Research, Workshop and Conference Proceedings, vol. 15, pp.461-469,2011. (Also, AISTATS 2011, Oral, acceptance rate 8.1%).
48.XiangyangLiu, Hongtao Lu. Group Sparse Non-negative Matrix Factorization forMulti-Manifold Learning. BMVC2011.
49.QingZhang, Hao Hu, Hongtao Lu, A robust method for real-time detecting and countingpeople. International Conference on Information and Multimedia Technology,ICIMT2011, Dubai, 2011.
50.HuZhiwei, Pan Zhifang, Lu Hongtao, Li Wenbin. Classification of Alzheimer’sdisease based on cortical thickness using AdaBoost and combination featureselection method. Communications in Computer and Information Science, v 234CCIS, n PART 4, p 392-401, 2011.
51.XiangyangLiu, Hongtao Lu, Wenbin Li, “Multi-manifold modeling for head pose estimation”,ICIP2010, pp. 3277-3280, 2010.
52.XinShu, Yao Gao and Hongtao Lu,”Face recognition via robust face representationand compressive sensing”, The 2010 International Symposium on IntelligentSignal Processing and Communication Systems (ISPACS2010).
53.JiongyunXie and Hongtao Lu, “Sparse Deep Belief Net for Handwritten DigitsClassification”, Accepted by the 2010 International Conference on WebInformation Systems and Mining and The 2010 International Conference onArtificial Intelligence and Computational Intelligence (WISM’10-AICI’10).
54.Fu,Zhenyong, Lu, Hongtao, Deng, Nan, Cai, Nengbin, “Four-level video summarycoding”, 2010 3rd International Congress on Image and Signal Processing, CISP2010, pp 261-264,2010/10/16(EI).
55.Fu, Z., Lu, H.,Deng, N., Cai, N., “Large scale visual classification via learneddictionaries and sparse representation”, 2010 International Conference onArtificial Intelligence and Computational Intelligence, AICI 2010, pp321-330,2010/10/23(Scopus).
56.XiangyangLiu, Hongtao Lu and Daqiang Zhang, “Head Pose Estimation based on ManifoldEmbedding and Distance Matric Learning”, Ninth Asian Conference on ComputerVision (ACCV2009), Xi’an, China, Sep. 23-27, 2009. (Best paper award)(Oral, Oral acceptance rate 5%)
57.XiangyangLiu, Hongtao Lu and Heng Luo, “Smooth Multi-Manifold Embedding for RobustIdentity-Independent Head Pose Estimation,” The 13th International Conferenceon Computer Analysis of Images and Patterns (CAIP2009), 66-73, Munster,Germany, Sep. 2nd-4th, 2009.
58.XiangyangLiu, Hongtao Lu and Heng Luo, “A New Representation Method of Head Images for HeadPose Estimation,” in Proc. IEEE International Conference on ImageProcessing (ICIP2009), Cairo, Egypt, Nov. 7-11, 2009.
59.GangYu，HongtaoLu， Illumination Invariant ObjectTracking with Incremental Subspace Learning， The5th International Conference on Image and Graphics(ICIG2009), Xi’an, Nov.20-23,2009.
60.GangYu， Zhiwei Hu and Hongtao Lu, Robust Incremental Subspace Learningfor Object Tracking. 16th International Conference on Neural InformationProcessing ICONIP2009, Part I, LNCS 5863, pp.819-828..
61.Tianwen Zhao,Qijun Zhao, Hongtao Lu and David Zhang, “Bagging Evolutionary featureExtraction Algorithm for Classification,” The 3rd InternationalConference on Natural Computation (ICNC’07).
62. QijunZhao, Hongtao Lu, and David Zhang, “Parsimonious Feature Extraction based onGenetic Algorithms and Support Vector Machines,” ISNN2006,LNCS 3971,pp.1387-1393, Part 1, 2006.
63.Qijun Zhao andHongtao Lu, “GA-driven LDA in KPCA Space for Facial Expression Recognition,”ICNC2005, LNCS 3611, 2005, pp. 28-36
64. Qijun Zhao,David Zhang, and Hongtao Lu, “Supervised LLE in ICA Space for Facial ExpressionRecognition,” ICNN&B2005, vol. 3, pp. 1970-1975.


早期论文：
神经网络和混沌
1. Xiangjun Wu, Hui Wang, Hongtao Lu. Modified generalizedprojective synchronization of a new fractional-order hyperchaotic system andits application in secure communication. Nonlinear Analysis: Real World Applications，v 13, n 3, p 1441-1450, June，2012.（SCI，影响因子：2.138）
2. Xiangjun Wu, Hongtao Lu. Outer synchronization of uncertaingeneral complex delayed networks with adaptive coupling. Neurocomputing，v 82, p 157-166, April 1, 2012.（SCI，影响因子：1.429）
3. Wu Xiangjun， Lu Hongtao. Generalizedfunction projective (lag, anticipated and complete) synchronization between twodifferent complex networks with nonidentical nodes. Communications in Nonlinear Science andNumerical Simulation, v 17, n 7, p 3005-3021, July 2012.
4. Xiangjun Wu, Darong Lai, Hongtao Lu. Generalizedsynchronization of the fractional-order chaos in weighted complex dynamicalnetworks with nonidentical nodes. Nonlinear Dynamics.（SCI，影响因子：1.741）
5. Darong Lai, Xiangjun Wu, Hongtao Lu, Christine Nardini.Learning overlapping communities in complex networks via non-negative matrixfactorization. International Journal of Modern Physics C, Vol. 22, No. 10 (2011) 1173-1190. （SCI，影响因子：1.260）
6. XiangjunWu, Hongtao Lu. Cluster synchronization in the adaptive complex dynamicalnetworks via a novel approach. Physics Letters A. 2011, 375(14): 1559-1565.（SCI，影响因子：1.963）
7. Xiangjun Wu, Hui Wang, Hongtao Lu. Hyperchaotic securecommunication via generalized function projective synchronization. NonlinearAnalysis: Real World Applications. 2011, 12(2): 1288-1299.（SCI、EI，影响因子：2.138）
8. Xiangjun Wu, Hongtao Lu. Generalized projective lagsynchronization between different hyperchaotic systems with uncertainparameters. Nonlinear Dynamics. 2011, 66(1-2): 185-200.（SCI、EI，影响因子：1.741）
9. Xiangjun Wu, Hongtao Lu. Adaptive generalized functionprojective lag synchronization of different chaotic systems with fullyuncertain parameters. Chaos Solitons & Fractals. 2011, 44(10): 802-810.（SCI，影响因子：1.267）
10. Wu X, Lu H. “Generalized projective synchronizationbetween two different general complex dynamical networks with delayedcoupling”. Physics Letters A, Volume 374, Issue 38, 2010, Pages 3932-3941.
11. Wu X, Lu H. “Exponential synchronization ofweighted general delay coupled and non-delay coupled dynamical networks”. Computers& Mathematics with Applications, Volume 60, Issue 8, 2010, Pages2476-2487.
12. Wu X, Lu H. “Outer synchronization between twodifferent fractional-order general complex dynamical networks”. ChinesePhysics B, Volume 19, Issue 7, 2010, Pages 070511.
13. Xiangjun Wu, Hongtao Lu, Shilei Shen, Synchronization of a newfractional-order hyperchaotic system. Physics Letters A, 373(2009)2329-2337.
14. Hongtao Lu, Guanrong Chen, “Global synchronization in an array of linearlycoupled delayed neural networks with an arbitrary coupling matrix,” InternationalJournal of Bifurcation and Chaos, vol.16, no.11, pp.3357-3368, 2006.
15. Hongtao Lu and Shun-ichi Amari, “Global exponential stability of multi-timescale competitive neural networks with nonsmooth functions,” IEEETransactions on Neural Networks, vol.17, no.5, pp.1152-1164, Sep. 2006.
16. Hongtao Lu and C.A. Leeuven, “Synchronization of chaotic neural networksvia output or state coupling,” Chaos, Solitons and Fractals,30(2006)166-176.
17. Hongtao Lu and Guanrong Chen, “Global exponential convergence ofmulti-time scale neural networks,” IEEE Transactions on Circuits and SystemsII, vol.52, no.11, pp.761-765, November, 2005.
18. Hongtao Lu, “Global exponential stability analysis of Cohen-Grossbergneural networks,” IEEE Transactions on Circuits and Systems II, vol.52,no.9, pp.476-479, August, 2005.
19. Hongtao Lu，“Comments on ‘A GeneralizedLMI-Based Approach to the Global Asymptotic Stability of Delayed CellularNeural Networks’”，IEEE Transactions on NeuralNetworks, vol.16, no.3, pp.778-779, May, 2005.
20. Hongtao Lu, Ruiming Shen and Fulai Chung, “Global exponential convergenceof Cohen-Grossberg neural networks with time delays,” IEEE Transactions onNeural Networks, vol.16, no.6, pp.1694-1696, November, 2005.
21. Hongtao Lu, Ruiming Shen, and Fu-Lai Chung, “Absolute exponentialstability of a class of recurrent neural networks with multiple and variabledelays,” Theoretical Computer Science, 344(2005)103-119.
22. HongtaoLu and XinzhenYu，Local bifurcations in delayedchaos anticontrol systems, Journal of Computational and Applied Mathematics,181(2005)188-199.
23. Hongtao Lu and Zhenya He, “Global exponential stability of delayedcompetitive neural networks with different time scales,” Neural Networks,18(2005)243-250.
24. Hongtao Lu, Absolute exponential stability analysis of delayed neuralnetworks, Physics Letters A, 336(2005)133-140.
25. Hongtao Lu, Zhenya He and Fulai Chung， Some sufficient conditions for exponential stability of delayedneural networks. NeuralNetworks, vol.17,pp.537-544, 2004.
26. Hongtao Lu and K. S. Tang, Chaotic Phase Shift Keying in DelayedChaotic Anticontrol Systems, International Journal of Bifurcation and Chaos，vol.12, no.5, 1017-1028, 2002.
27. Hongtao Lu, Chaotic attractors in delayed neural networks. Physics Letters A, 298（2002）109-116.
28. Hongtao Lu. Stability criteria for delayed neural networks. Physical Review E, vol.64,051901-1-051901-13,2001.
29. Hongtao Lu, On stability of nonlinearcontinuous-time neural networks with delays. Neural Networks,vol. 13, 1135-1143, 2000.
30. Hongtao Lu, Yongbao Heand Zhenya He, A chaotic generator: Analysis of the dynamic behaviour of acellular neuron with delay. IEEE Transactions on Circuits and Systems,no. 2, pp.178-181,1998.
31. Hongtao Lu, Zhenya He, Chaotic Behavior in First-Order Autonomous Continuous-Time Systems with Delay. IEEE Transactions onCircuits and Systems, vol.43, no. 8, pp.700-702, 1996.
32. Hongtao Lu, Zhenya He,Synchronization of chaotic systems based on system partitionapproaches. Physics Letters A,vol.219, pp.271-276, 1996.



复杂网络
1. Darong Lai, XiangjunWu and Hongtao Lu, Learning Overlapping Communities in Complex Networks viaNon-negative Matrix Factorization. International Journal of Modern Physics C,Vol. 22, No. 10 (2011) 1173-1190.
2. Darong Lai, XinyiYang, Gang Wu, Yuanhua Liu and Christine Nardini, Inference of Gene Networks-applicationto Bifidobacterium, Bioinformatics, vol.27, No.2, pp. 232-237, 2011.
3. Darong Lai, ChristineNardini and Hongtao Lu, Partitioning networks into communities by messagepassing, Physical Review E, vol.83, 016115, 2011.
4. Darong Lai, HongtaoLu and Christine Nardini, Enhanced modularity-based community detection byrandom walk network preprocessing, Physical Review E, vol.81, 066118, 2010.
5. Darong Lai, HongtaoLu and Christine Nardini, Extracting weights from edge directions to findcommmunities in directed networks, Journal of Statistical Mechanics: Theory andExperiment, 2010, P06003.
6. Darong Lai, HongtaoLu and Christine Nardini, Finding communities in directed networks by PageRankrandom walk induced network embedding, Physica A: Statistical Mechanics and itsApplications, vol. 389, pp. 2443-2454, 2010.
7. Darong Lai, HongtaoLu, Mario Lauria, Diego di Bernardo and Christine Nardini, MANIA: A genenetwork reverse algorithm for compounds mode-of-action and genes interactionsinference, Advances in Complex Systems, vol. 13, issue 1, pp83-94, 2010 .
8. GangYu, Xianpeng Wang and Hongtao Lu, Efficient routing strategy on scale-freenetwork. Modern physics letters B, Vol. 23, No. 11(2009)1377-1389.
9. XianpengWang, Gang Yu and Hongtao Lu, A localinformation-based routing strategy on the scale-free network. Modern physicsletters B, Vol. 23, No. 10 (2009)1291-1301.
10. DarongLai, Hongtao Lu, Indenification of community structure in complex networks usingaffinity propagation clustering method. Modern physics letters B, Vol. 22, No. 16 (2008) 1547-1566.
11. Xutao Wang, GuanrongChen and Hongtao Lu, A very fastalgorithm for detecting community structures in complex networks. Physica A, Vol. 384, Issue 2, pp.667-674,15 October 2007.
12. Xutao Wang,Hongtao Lu, and Guanrong Chen, TheModeling of Weighted Complex Networks. ModernPhysics Letters B，vol.21,No.16, pp.2813-2820,2007. （SCI检索）
13. Xuan Guo, Hongtao Lu, Traffic Congestion Analysis in ComplexNetworks Based on Various Routing Strategies. Modern Physics Letters B， Vol.21, No.15, pp.929-939, 2007. （SCI检索）


数字水印
1. He,Zhongwei; Sun, Wei; Lu Wei; Lu, Hongtao.Digital image splicing detection based on approximate run length. Patternrecognition letters, vol: 32, no: 12, pages:1591-1597 DOI: 10.1016/j.patrec.2011.05.013,2011.
2. Wei Lu, Wei Sun, Fu-Lai Chungand Hongtao Lu. Revealing digital fakeryusing multiresolution decomposition and higher order statistics. Engineeringapplications of artificial intelligence, vol.24, no.4, page. 666-672, JUN 2011.
3. WeiLu, Hongtao Lu and Fu-Lai Chung, “Feature based robust watermarking using imagenormalization”, Computers and Electrical Engineering,36(2010)2-18.
4. WeiLu, Wei Sun and Hongtao Lu, “Robust watermarking based on DWT and nonnegativematrix factorization”, Computers and Electrical Engineering, 35(2009)183-188.
5. Qijun Zhao,Hongtao Lu, “PCA-based web page watermarking,” Pattern Recognition, 40 (2007) 1334-1341.
6. Wei Lu, Fu-Lai Chung, Hongtao Lu and Kup-Sze Choi, Detecting Fake Images Using Watermarks and SupportVector Machines. Computer Standard and Interface，30（2008）132-136.
7. Wei Lu, Hongtao Lu and Fu-LaiChung, “Novel robust image watermarking using difference correlation detector,”Computer Standards & Interfaces, vol. 29, no.1, pp.132-137, Jan. 2007.
8. Wei Lu, Hongtao Lu and Fu-LaiChung, “Robust digital image watermarking based on subsampling,” AppliedMathematics and Computation, vol. 181, no.2, pp.886-893, Oct., 2006.
9. Wei Lu, Hongtao Lu and Fu-LaiChung, “Feature based watermarking using template match,” Applied mathematics and computation177(1):377-386, Jun. 2006.
10. Wei Lu, Fu-Lai Chung and Hongtao Lu,“Blind fake image detection scheme using SVD,” IEICE Trans. Communications,vol. E89-B, no. 5, pp.1726-1728, May, 2006.
11. Ronghua Yao,Qijun Zhao, and Hongtao Lu, "A Novel Watermark Algorithm for IntegrityProtection of XML Documents," International Journal of Computer Scienceand Network Security, vol. 6, no. 2B, February 2006, pp. 202-207
12. Qijun Zhao,Hongtao Lu, “A PCA-based watermarking scheme for tamper-proof of web pages,” Patternrecognition, 38(2005)1321-1323.
13. Zhao Qijun, LuHongtao, Jiang Xiaohua, “Web page watermarking for tamper-proof,” Journal ofShanghai Jiao Tong University, vol.E-10, no.3, pp.280-284, Sep., 2005.
14. Wei Lu,Hongtao Lu and Fu-Lai Chung, “Attacking subsampling-based watermarking,” IEICETransactions on Fundamentals of Electronics, Communications and ComputerSciences, Vol.E88-A, no.11, pp.3239-3240, 2005.
15. Ruiming Shen, Yonggang Fu andHongtao Lu, “A Novel Image Watermarking Scheme based on Support VectorRegression,” Journal of systems and software, vol. 78, no.1, pp.1-8, Oct.,2005.
16. Hongtao Lu, Ruiming Shen and Fu-lai Chung, “A fragile watermarkingscheme for image authentication,” Electronics Letters，vol.39, no.12,pp.898-900,2003.
17. Y.Fu, R.Shen and H.Lu, “Watermarkingscheme based on support vector machine for colour images,” Electronics Letters,vol.40, no.16, pp.986-987，2004.
18. Qiu Yunjie, Lu Hongtao, Deng Nan, Cai Nengbin. A robust imagewatermarking shceme based on template in LAB color space. Communicationsin Computer and Information Science, v 234 CCIS, PART4, p 402-410, 2011.
19. 董冰峰，邱赟捷，卢宏涛，邓南，蔡能斌, 基于HSV 颜色空间的彩色图像的盲水印算法研究. 计算机应用与软件，第28卷第2期，1-3页，2011年。
20. Peng Sun, Hongtao Lu, Two efficient fragile web watermarkingschemes, Fifth International Conference on Information Assurance andSecurity(IAS2009), vol. 2, pp.326-329, August 18-20, Xi’an China, 2009.
21. Peng Sun, Hongtao Lu, An efficient web page watermarking scheme. 20092nd IEEE International Conference on Computer Science and InformationTechnology(ICCSST2009), pp.163-167, 2009.
22. Liu,Xiangyang, Lu, Hongtao，Fragile Watermarking Schemes forTamperproof Web Pages. ISNN 2008, Part II, LNCS 5264, pp 552-559, 2008.
23. WeiLu, Wei Sun, Ji-wu Huang, Hongtao Lu, Digital image forensics using statisticalfeatures and neural network classifier. the Seventh International Conference onMachine Learning and Cybernetics, 2008，2831-2934.
24. WeiLu, Wei Sun, and Hongtao Lu, Blind Image Watermark Analysis Using FeatureFusion and Neural Network Classifie. International Symposium on Neural Networks2008，LNCS5264：237-242.
25. Wei Lu and Hongtao Lu，Content Dependent Image Watermarking using Chaos andRobust Hash. 2007InternationalConference on Computational Intelligence and Security (CIS2007).
26. Wei Lu, Hongtao Lu and Fu-lai Chung, “Robust image watermarkingusing RBF neural network,” LNCS 3972, pp.623-628, 2006. ( ISNN2006)
27. Wei Lu, Fu-lai Chung and Hongtao Lu, “Image fakery and neural network-based detection,” LNCS 3972,pp.610-615, 2006. (ISNN2006)
28. Wei Lu, Hongtao Lu and Fu-lai Chung, “Chaos-based spread spectrumrobust watermarking in DWT domain,” Proc. of the fourth international conferenceon machine learning and cybernetics, Guangzhou, vol.9, pp. 5308-5313, 2005.
29. Wei Lu, Hongtao Lu and Fu-lai Chung, “Subsampling-based Robust Watermarking Using Neural NetworkDetector”. ISNN2005, LNCS 3497, pp.801-806, 2005.
30. Yonggang Fu, Ruiming Shen, Hongtao Lu and Xusheng Lei, “SVR-basedoblivious watermarking scheme,” ISNN2005, LNCS 3497, pp.789-794,2005.
31. Wei Lu, Hongtao Lu and Ruiming Shen,“Color Image Watermarking Based on Neural Networks”. Proc. of ISNN2004, Lecture Notes inComputer Science, 3174:651-656 2004.
32. Yonggang Fu, Ruimin Shen, Hongtao Lu, “Optimal watermark detectionbased on support vector machines”. Proc. of ISNN2004, Lecture Notes in Computer Science 3173: 552-557 2004.
33. 卢宏涛，卢伟，“基于混沌映射的一种图像脆弱水印方案’’。 2003中国计算机大会(CNCC2003),vol. 1, pp. 160-163。



脑电信号处理
1. Jing-Nan Gu, Hong-Jun Liu, Hong-Tao Lu and Bao-Liang Lu, “An IntegratedHierarchical Gaussian Mixture Model to Estimate Vigilance Level Based on EEGRecordings,” ICONIP, Shanghai, China, 2011.
2. HongbinYu, Hongtao Lu, Vigilance Estimation Based on Statistic Learning with One ICA Component ofEEG Signal. ICONIP, Shanghai, China, 2011.
3. Hong-BinYu, Hong-Tao Lu ,Tian Ouyang, Hong-Jun Liu, Bao-Liang Lu, “Vigilance DetectionBased on Sparse Representation of EEG,” International Conference of the IEEEEngineering in Medicine and Biology Society, Buenos Aires, Argentina, Sep.,2010.
4. TianOuyang, Hong-Tao Lu, Bao-LiangLu, “Vigilance Analysis Based on EEG Signals: Seeking for Suitable Features,” Journal of Biological Systems, vol.18, pp. pp. 81-99, 2010.
5. Tian Ouyang, Hong-Tao Lu, “Vigilance Analysis Based onContinuous Wavelet Transform of EEG Signals,” International Conference ofBiomedical Engineering and Computer Science, Wuhan, China, 2010.
6. Hongjun Liu, Qingsheng Ren, and Hongtao Lu, Estimatingvigilance in driving simulation based on detection of light drowsiness. Internationalconference on bioinformatics 2010, pp. 131-134，Valencia, Spain, 2010.
7. Hong-Jun Liu, Hong-Bin Yu, Qing-Sheng Ren, Hong-Tao Lu,“Estimate Vigilance Level in Driving Simulation Based on SparseRepresentation,” International Conference on Machine Learning and Cybernetics,Qingdao, China, 2010.
8. Jun Pan, Qing-Sheng Ren,Hong-Tao Lu,“Vigilance analysis based on fractal features of EEGsignals,” Computer Communication Control and Automation, Taiwan, China, 2010.


纵向项目：
1.深度神经网络压缩及其应用研究（国家自然科学基金面上项目，2018-2021，主持）
2. 基于深度学习的骨肿瘤诊断方法研究（国家自然科学基金面上项目，2019-2022，参与）
3. 泛在信息制造环境下的机器人群智视觉交互与优化控制 （国家自然科学基金重点项目，参与）
4. 大数据表示与计算的新型理论和算法研究（上海市重点基础项目，2017-2019，主持）
5. 中枢损伤后瘫痪肢体功能重建和意识障碍唤醒新技术的研发和临床应用 （863重点项目，2015-2018，参与）
6. 低秩距离学习及其应用 （国家自然科学基金面上，2013-2016，主持）
7. 基于机器学习的复杂网络社团结构分析及其应用研究 （国家自然科学基金，2009-2011，主持）
8. 基于脑电信号和视频人脸图像的警觉度标注、估计与实时监测技术研究 （863项目，2008-2010，主持）

部分横向项目：
1. 监控视频在线优化技术
2. 密集场景人群计数和定位技术研究
3. 基于深度学习的图像与视频Captioning
4. 深度学习在计算机视觉中的应用研究
5. 票据图像自动识别方法

1. 神经网络的非线性理论及其在信息隐藏、模式识别中的应用，上海市自然科学奖二等奖，2010年，排名第一。
2. 复杂混沌动态网络系统的同步控制与应用，河南省科技进步奖二等奖，2015年，排名第二。
3. 司法数码影像防伪信息技术研究，上海市科技进步奖三等奖，2016年，排名第三。
4. 连续入选2014-2019Elsevier计算机科学中国高被引****榜单。
5. ACCV 2009最佳论文奖。
6. CAISSE 2012最佳论文奖。
7. 2005入选教育部新世纪优秀人才计划。
8. 2003入选上海市曙光****。
9. SCI他引1360+，GoogleScholar引用4000+，H-index 37。

PC members: AAAI, ISNN, IJCNN，ICONIP，ICIST 等。
信号采集与处理编委
视觉计算与认知专委，CCA生物控制论与BME专委