Faculty

Lu Hongtao Professor

MainPage:

Office Telephone: +86-21-3420-4879

Office Address: SEIEE-3-425

Email: lu-ht@cs.sjtu.edu.cn

Lab: The China Ministry of Education (MOE) - Microsoft Key Laboratory of Intelligent Computing and System; Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering (IICE)

  • Research
  • Education
  • Work Experience
  • Teaching Assignment
  • Publications
  • Project Fund
  • Awards
  • Academic Service

     Hongtao Lu is a professor at the department of computer science and engineering, Shanghai Jiao Tong University. His research interests include machine learning, deep learning, computer vision and pattern recognition. He has authored or co-authored more than 100 research papers in journals and conference such as IEEE Transactions, Pattern Recognition, CVPR, ECCV, AAAI etc. His published papers have gotten more than 1300 citations from Web of Science, and more than  4000 citations from Google Scholar, his H-index is 37. He had served as PIs for dozens of projects from NSFC, Ministry of Science and Technology, Ministry of Education, Municipal Government of Shanghai, and industries. He has been continuously listed among the most cited researchers in computer science in China by Elsevier from years of 2014 to 2018. He also got several research awards from the government.

    Under his supervision, 13 students got their Ph.D degrees, 58 got Master degrees, and 35 part-time Master degrees. Some of his students already held a professor position in 985, 211universities of China. Many of his master students are hired by big companies such as Huawei, Baidu, Alibaba, Tencent, Google, Microsoft and Facebook etc. Currently, there are 11 Ph.D. students and 9 Master students in his Lab, including 5 international students. He had also supervised 58 undergraduate students for their Bachelor degree theses. Many of them are pursuing their higher degrees in facous universities scu as Stanford, MIT and CMU etc. 

Ph.D. degree in Radio Engineering and Signal Processing from Southeast university, Nanjing, China, in 1997

M.S. degree in Mathematics from Sichuan normal university, Chengdu, China, in 1990. 

B.S. degree in Mathematics from Sichuan normal university, Chengdu, China, in 1987.

2001 to present, professor, the department of computer science and engineering, Shanghai Jiao Tong university, Shanghai, China.

1999-2001, associate professor, the department of computer science and engineering, Shanghai Jiao Tong university, Shanghai, China.

1997-1999, post doctoral fellow, the department of computer science, Fudan university, Shanghai, China.

1990-1993, lecture, the department of mathematics, Chuxiong normal university, Yunnan province, China. 


Visiting experiences

2001,2002,2004,2005, visiting scholar in City University of Hong Kong, the Hong Kong Polytechnic University, RIKEN (Japan)

Discrete mathematics  (undergraduate course)

Artificial intelligence (undergraduate course)

Digital image processing (postgraduate course)

Image processing and machine vision (postgraduate course)

Mathematic foundations in computer science (course for ACM honored classes)

Selected publications(Machine learning, Computer vision)


1.    Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, Baining Guo. Learning Texture Transformer Network for Image Super-Resolution. CVPR 2020.  

2.    Yaoyi Li, Hongtao Lu. Natural Image Matting via Guided Contextual Attention. AAAI 2020.  

3.    Li Wang, Zechen Bai, Yonghua Zhang, Hongtao Lu. Show, Recall, and Tell: Image Captioning with Recall Mechanism. AAAI 2020.  

4.    Yiru Zhao, Xu Shen, Zhongming Jin, Hongtao Lu, Xiansheng Hua. Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification. CVPR 2019.  

5.    Yu Qin, Jiajun Du, Yonghua Zhang, Hongtao Lu. Look Back and Predict Forward in Image Captioning. CVPR 2019.  

6.    Yiru Zhao, Zhongming Jin, Guojun Qi, Hongtao Lu, Xuansheng Hua. An adversarial approach to hard triplet generation. ECCV 2018.  

7.    Fei Jiang, Xiangyang Liu, Hongtao Lu, Ruiming Shen. Efficient Multi-dimensional Tensor Sparse Coding Using t-linear Combination. AAAI 2018.  

8.    Yiru Zhao, Bing Deng, Jianqiang Huang, Hongtao Lu, Xiansheng Hua. Stylized Adversarial AutoEncoder for Image Generation. Proceedings of the 2017 ACM on Multimedia Conference (MM ’17). ACM, Mountain View, California, USA, 2017.10.23-10.27, 244-251.  

9.    Yiru Zhao, Chen Shen, Yao Liu, Hongtao Lu, 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. 

10.    Zihao Hu, Junxuan Chen, Hongtao Lu, Tongzhen Zhang. Bayesian Supervised Hashing. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2017), pp. 4321-4328.  

11.    Qi Liu, Hongtao Lu. Natural supervised Hashing, IJCAI 2016 (Oral).  

12.    Junxuan Chen, Baigui Sun, Hao Li, Hongtao Lu, Xian-Sheng Hua. Deep CTR Prediction in Display Advertising. ACM Multimedia 2016 (oral).  

13.    Yiru Zhao, Yaoyi Li, Zhiwen Shao, Hongtao Lu. LSOD: Local Sparse Orthogonal Descriptor for Image Matching. ACM Multimedia, 2016.  

14.     Kang Zhao, Hongtao Lu. Locality Preserving Hashing. AAAI 2014.  

15.    KangZhao, Hongtao Lu. Locality Preserving Discriminative Hashing. ACM Multimedia, 2014. 

16.    Zhenyong Fu, Hongtao Lu, Horace Ip. Modalities Consensus for Multi-Modal Constraint Propagation. ACM Multemedia 2012, 773-776. 

17.    Zhenyong Fu, Horace H.S. Ip, Hongtao Lu, and Zhiwu Lu. Multi-model Constraint Propagation for Image Clustering. ACM  Multimedia 2011.  Long Paper, Oral.Acce ptance rate for long paper 13% 

18.    Zhenyong Fu, Horace H.S. Ip, Hongtao Lu. Symmetric Graph Regularized Constraint Propagation. AAAI2011, pp.350-355,2011.  

19.    Wei He, Takayoshi, Hongtao Lu, and Shihong Lao,  “SURF tracking,”  the twelfth International Conference on Computer Vision (ICCV2009,  acceptance rate 12%), Kyoto, Japan,Sep.29-Oct.2, 2009. 

20.    Qijun Zhao, David Zhang and Hongtao Lu,  A direct evolutionary feature extraction algorithm for classifying high dimensional data. AAAI’06, pp.561-566,2006.  

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 scale search. IEEE Transactions on Multimedia, VOL. 19, NO. 8, AUGUST 2017, pp. 1785-1797.

23.    Hongbin Yu, Hongtao Lu. Orthogonal optimal reverse prediction for semi-supervised learning. Pattern recognition, 60(2016) 908-920.

24.    Hongtao Lu, ZhenyongFu, XinShu. Non-negative and sparse spectral clustering. Pattern Recognition, Pattern Recognition, 47(2014)418–426. 


 

Other publications (Machine learning, Computer vision)


Journal papers  

1.     Yiru Zhao, Hongtao Lu. Neighbor similarity and soft-label adaptation 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 With Applications to Vigilance Detection. IEEE Access 7: 111102-111114 (2019)

3.    Qing Guan, Yunjun Wang, Jiajun Du, Yu Qin, Hongtao Lu, Jun Xiang, Fen Wang. Deep learning based classification of ultrasound images for thyroid nodules: a large scale of pilot study. Annals of Translational Medicine, 2019;7(7):137.

4.    Qing Guan, Xiaochun Wan, Hongtao Lu, Bo Ping, Duanshu Li, Li Wang, Yunjun Wang, Jun Xiang. Deep convolutional neural network Inception-v3 model for differential diagnosing of lymph node in cytological images: a pilot study. 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-16 model for differential diagnosing of papillary thyroid carcinomas in cytological images: a pilot study. Journal of Cancer 2019, Vol. 10:4876.

6.    Zhenyong Fu, Lu Zhiwu, Horace Ip, Hongtao Lu, 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 concept factorization for data representation. Neural Networks 52(2014)1-17.

8.     Xianzhong Long, Hongtao Lu, Yong Peng, Wenbin Li.  Graph regularized discriminative non-negative matrix factorization for face recognition. Multimedia tools and applications, (2014)72:2679-2699.

9.     Xin Shu, Hongtao Lu. Linear discriminant analysis with spectral regularization. Applied intelligence, accepted.

10.     Wei Huang, Hongtao Lu. Automatic defect classification of TFT-LCD panels with shape, histogram and color features. International Journal of Image and Graphics, Vol. 13, No. 3 (2013) 1350011.

11.    Yangcheng He, Hongtao Lu, Saining Xie. Semi-supervised Non-negative Matrix Factorization for Image Clustering with Graph Laplacian. Multimedia Tools and Applications. 2013, DOI10.1007/s11042-013-1465.

12.     Xianzhong Long, Hongtao Lu, Wenbin Li. Image classification based on nearest neighbor basis vectors. Multimedia Tools and Applications. 2012, DOI10.1007/s11042-012-1289-4.

13.    Jingnan Gu, Hongjun Liu, Hongtao Lu and Baoliang Lv. An integral Gaussian mixture model to estimate vigilance level based on EEG Recordings. Neurocomputing 129(2014)107–113.

14.    Pan Zhifang, Lu Hongtao, Cheng Qi. Activity of daily living and lesion position among multiple sclerosis patients by Bayes network. Neural Regeneration Research, 8(14):1327-1336,2013.  

15.    Xin Shu,Yao Gao,Hongtao Lu, Efficient linear discriminant analysis with locality preserving for face recognition. Pattern Recognition, v 45, n 5, p 1892-1898, May 2012.

16.    Yu Gang; Hu Zhiwei; Lu Hongtao. Robust object tracking with occlusion handle. Neural computing&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 Learners and Construct Learning Communities. Chinese journal of electronics, vol. 20, no. 2, pp. 207-211, APR 2011.

18.     Pan zhifang, Hu zhiwen, Lu Hongtao. Classification of alzheimer’s disease using a novel PCA method based on matrix factorization. International Journal of Advancements in Computing Technology, v 3, n 10, p 283-290, November 2011.

19.     Zhenyong Fu, Hongtao Lu, and Wenbin Li. Incremental Visual Objects Clustering with the Growing Vocabulary Tree. Multimedia and applications. DOI 10.1007/s11042-010-0616-x, 2010.

20.     Tian Ouyang, Hong-Tao Lu, Bao-Liang Lu, “Vigilance Analysis Based on EEG Signals: Seeking for Suitable Features,” Journal of Biological Systems, vol.18, 2010.  

21.     Qijun Zhao, David Zhang, L. Zhang and Hongtao Lu “Evolutionary Discriminant Feature Extraction with Application to Face Recognition,” EURASIP Journal on Advances in Signal Processing, vol.2009, paper ID 465193. 

22.     Qijun Zhao, Hongtao Lu and David Zhang, “A fast evolutionary pursuit algorithm based on linearly combining vectors,” Pattern recognition, 39(2006) 310-312.


Conference papers

1.    Yaoyi Li, Jianfu Zhang, Weijie Zhao, Weihao Jiang and Hongtao Lu. Inductive guided filter: real-time deep matting with weakly annotated masks on mobile devices. ICME 2020.  

2.    Chang Liu, Hongtao Lu.  A highly efficient trainig-aware convolutional neural network compression paradigm. ICME Workshop, 2020.

3.    Weihao Jiang, Zhaozhi Xie, Yaoyi Li, Chang Liu, Hongtao Lu. LRNNET: A light-weighted network with efficient reduced non-local operation for real-time semantic segmentation. ICME Workshop, 2020.

4.    Meng Zhou, Yaoyi Li, Hongtao Lu, CaiNengbin, ZhaoXuejun. Semi-Supervised Meta-Learning via Self-Training. ISA 2020.

5.    Haotian Tang, Yiru Zhao, Hongtao Lu. Unsupervised Person Re-Identification with Iterative Self-Supervised Domain Adaptation. CVPR Workshop, 2019.

6.    Usman Ali, Bayram Bayramli and Hongtao Lu. Temporal Continuity Based Unsupervised Learning for Person Re-Identification. ICONIP 2019.

7.    Zhenru Li, Yaoyi Li, Hongtao Lu and Usman Ali. Improve Image Captioning by self-attention. ICONIP 2019.

8.    Yu Qin, Jiajun Du, Xinyao Wang, Hongtao Lu. Recurrent Layer Aggregation using LSTM. IJCNN, 2019.

9.    Jiajun Du, Yu Qin, Hongtao Lu, Network Search for Binary Networks. IJCNN, 2019.

10.    Bayram Bayramli, Hongtao Lu. FH-GAN: Face Hallucination and Recognition using Generative Adversarial Networks. ICONIP 2019. 

11.    Wenbo Li, Hongtao Lu. Multi-level Collaborative Attention Network for Person Search. ACCV 2018.

12.    Kaicheng Tang, Xiaohua Shi, Hongtao Lu. Image recognition with deep learning for library book identification. 19th Pacific-Rim Conference on Multimedia, PCM 2018.

13.    Fei Jiang, Xiao-Yang Liu, Hongtao Lu, Ruimin Shen. Anisotropic total variation regularized low-rank tensor completion based on tensor nuclear norm for color image inpainting. ICASSP 2018.  

14.    Qite, Hongtao LuHuiyu Weng. Modeling Long Range Relations by Feature Translation. ICMV2018 The 11th International Conference on Machine Vision, 2018.

15.    Deyi Ji, Hongtao Lu, Tongzhen Zhang. End to end multi-scale convolutional neural networks for crowd counting. ICMV2018 The 11th International Conference on Machine Vision, 2018.

16.    Ze Chen, Hongtao Lu. Recurrent Spatiotemporal Feature Learning for Action Recognition. 2018 the 4th International Conference on Robotics and Artificial Intelligence - ICRAI 2018.

17.   Shicong Liu, Hongtao Lu. Space shuttle model: a physics inspired method for learning quantizable deep representations. Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2017, 10-14 July 2017, pp.121-126.  

18.    Shicong Liu, Hongtao Lu. Quantizable deep representation learning with gradient snapping layer for large scale search. Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2017, 10-14 July 2017, pp.1380-1385.  

19.    Hualong Huang, Bo Huang, Hongtao Lu, and Huiyu Weng. Stereo Matching using Conditional Adversarial Networks. International Conference on Neural Information Processing ICONIP 2017, pp 124-132.

20.    Bo Huang, Hualong Huang, and Hongtao Lu. Convolutional Gated Recurrent Units Fusion for Video Action Recognition. International Conference on Neural Information Processing ICONIP 2017, pp 114-123.

21.    Xiaohua Shi, Hongtao Lu, Guanbo Jia. Adaptive Overlapping Community Detection with Bayesian NonNegative Matrix Factorization. International Conference on Database Systems for Advnced Applications DASFAA, 2017, pp 339-353. 

22.    Yurun Shen, Hongtao Lu, Jie Jia. Classification of Motor Imagery EEG Signals with Deep Learning Models. International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017: pp 181-190.

23.     Junxuan Chen, Hongtao Lu. Online self-organizing hashing. ICME 2016.  

24.    Shicong Liu, Hongtao Lu. Generalized residual vector quantization for large scale data. ICME 2016. (Oral)  

25.     Yaoyi Li, Hongtao Lu. Adaptive Affinity Matrix for Unsupervised Metric Learning. ICME 2016. (Oral)   

26.     Mingxuan Di, Guang Yang, Qinchuang Zhang, Kang Fu, Hongtao Lu. Fast visual object tracking using convolutional filters. ICONIP, 2016.

27.    Yangcheng He, Hongtao Lu, Baoliang Lu. Graph regularized non-negative local coordinate factorization with pairwise constraints for image representation. ICME 2015. 

28.    Li Wu, Kang Zhao, Hongtao Lu_, Zhen Wei, Baoliang Lu. Distance preserving marginal hashing for image retrieval. ICME 2015.  

29.    Pan Chen, Yangcheng He, Hongtao Lu. Constrained Non-negative matrix factorization with graph Laplacian. ICONIP 2015.

30.    Xiaohua Shi, Hongtao Lu, Yangcheng He, Shan He. Community detection with pairwise constrained symmetric non-negative matrix factorization. ASONAM’15 Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pages 541-546, 2015.

31.    Xuejiao Bai, Xuan Luo, Shuo Li, Adaptive stereo matching by loop-erased random walk. ICIP 2014.

32.    Yuzhang Yuan, Hongtao Lu. Multi-label linear discriminant analysis with Locality Consistency. ICONIP, 2014.

33.    Dong Xing, Xianzhong Wang, Hongtao Lu. Action Recognition Using Hybrid Feature Descriptor and VLAD Video Encoding, ACCV Workshop 2014.

34.    Xianzhong Wang, Hongtao Lu, Xianzhong Long. Action recognition with uncertain VLAD. 2014 Seventh International Symposium on Computational Intelligence and Design, pp.185-188.

35.    Dengxiang Liu, Hongtao Lu. Layered Recommendation: a New Strategy for Movie Promotion. 2014 7th International Congress on Image and Signal Processing (CISP 2014), 2014.

36.    Zhuo Wang, Hongtao Lu. Online Recommender System Based on Social Network Regularization.  ICONIP(1) 2014: 487-494.

37.    Saining Xie, Jiashi Feng, Shuicheng Yan, Hongtao Lu. Perception Preserving Projections. BMVC (Oral), 2013.

38.    Shaokun Feng, Hongtao Lu. Image classification based on weight adjustment before feature pooling. ICONIP, 2013, Part III, LNCS 8228, pp. 360–367, 2013.

39.    Kang Zhao, 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 Factorization based on Spatial Pyramid Matching for Face Recognition. 2013 Fifth International Conference on Intelligent Human-Machine Systems and Cybernetics.

41.    Yi Ding, Hongtao Lu. Sparse Representations of Clustered Video Shots for Action Recognition. IEEE 3rd International Conference on Computer Science and Network Technology, 2013.

42.     Lei Huang, Zhifang Pan, Hongtao Lu. Automated Diagnosis of Alzheimer’s Disease with Degenerate SVM-based Adaboost. 2013 Fifth International Conference on Intelligent Human-Machine Systems and Cybernetics.

43.    Saning Xie, Hongtao Lu and Yangcheng He. Multi-Task Co-clustering via Nonnegative Matrix Factorization. International Conference on Pattern Recognition (ICPR2012), 2012.

44.     Lei Huang, Hongtao Lu, Wei Huang. Automated Defect Classification with SVM-based Adaboost. International Conference on Computer and Information Science, Safety Engineering (CAISSE2012). (Best paper award)

45.    Xianzhong Long, Hongtao Lu and Xin Shu. An Efficient Data Dimensionality Reduction Scheme based on SIFT for Face Recognition. 2012 International Conference on Web Information Systems and Mining (WISM’12) and the 2012 International Conference on Artificial Intelligence and Computational Intelligence (AICI’12). WISM’12-AICI’12, accepted.

46.    Xin Shu, Hongtao Lu. Neighborhood Structure Preserving Ridge Regression for Dimensionality Reduction. Chinese Conference on Pattern Recognition (CCPR 2012) accepted.

47.    Hongtao Lu, Xianzhong Long and Jingyuan Lv. A Fast Algorithm for Recovery of Jointly Sparse Vectors based on the Alternating Direction Methods. Journal of Machine Leaning Research, Workshop and Conference Proceedings, vol. 15, pp.461-469, 2011. (Also, AISTATS 2011, Oral, acceptance rate 8.1%).

48.    Xiangyang Liu, Hongtao Lu. Group Sparse Non-negative Matrix Factorization for Multi-Manifold Learning. BMVC2011.

49.    Qing Zhang, Hao Hu, Hongtao Lu, A robust method for real-time detecting and counting people. International Conference on Information and Multimedia Technology, ICIMT2011, Dubai, 2011.

50.    Hu Zhiwei, Pan Zhifang, Lu Hongtao, Li Wenbin. Classification of Alzheimer’s disease based on cortical thickness using AdaBoost and combination feature selection method. Communications in Computer and Information Science, v 234 CCIS, n PART 4, p 392-401, 2011.

51.    Xiangyang Liu, Hongtao Lu, Wenbin Li, “Multi-manifold modeling for head pose estimation”, ICIP2010, pp. 3277-3280, 2010.

52.    Xin Shu, Yao Gao and Hongtao Lu,”Face recognition via robust face representation and compressive sensing”, The 2010 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS2010).

53.    Jiongyun Xie and Hongtao Lu, “Sparse Deep Belief Net for Handwritten Digits Classification”, Accepted by the 2010 International Conference on Web Information Systems and Mining and The 2010 International Conference on Artificial Intelligence and Computational Intelligence (WISM’10-AICI’10).

54.    Fu, Zhenyong, Lu, Hongtao, Deng, Nan, Cai, Nengbin, “Four-level video summary coding”, 2010 3rd International Congress on Image and Signal Processing, CISP 2010, pp 261-264,2010/10/16(EI).

55.     Fu,Z., Lu,H.,Deng,N., Cai,N., “Large scale visual classification via learned dictionaries and sparse representation”,  2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010, pp 321-330,2010/10/23(Scopus).

56.    Xiangyang Liu, Hongtao Lu and Daqiang Zhang, “Head Pose Estimation based on Manifold Embedding and Distance Matric Learning”, Ninth Asian Conference on Computer Vision (ACCV2009), Xi’an, China, Sep. 23-27, 2009. (Best paper award)  (Oral, Oral acceptance rate 5%)

57.    Xiangyang Liu, Hongtao Lu and Heng Luo, “Smooth Multi-Manifold Embedding for Robust Identity-Independent Head Pose Estimation,” The 13th International Conference on Computer Analysis of Images and Patterns (CAIP2009), 66-73, Munster, Germany, Sep. 2nd-4th, 2009.

58.    Xiangyang Liu, Hongtao Lu and Heng Luo, “A New Representation Method of Head Images for Head Pose Estimation,” in Proc. IEEE International Conference on Image Processing  (ICIP2009), Cairo, Egypt, Nov. 7-11, 2009.

59.    Gang  YuHongtaoLu Illumination Invariant Object Tracking with Incremental Subspace Learning The 5th International Conference on Image and Graphics(ICIG2009), Xi’an, Nov.20-23, 2009.

60.    Gang Yu Zhiwei Hu and Hongtao Lu, Robust Incremental Subspace Learning for Object Tracking. 16th International Conference on Neural Information Processing ICONIP2009, Part I, LNCS 5863, pp.819-828..

61.    Tianwen Zhao, Qijun Zhao, Hongtao Lu and David Zhang, “Bagging Evolutionary feature Extraction Algorithm for Classification,”  The 3rd International Conference on Natural Computation (ICNC’07).

62.   Qijun Zhao, Hongtao Lu, and David Zhang, “Parsimonious Feature Extraction based on Genetic Algorithms and Support Vector Machines,” ISNN2006,LNCS 3971, pp.1387-1393, Part 1, 2006.

63.    Qijun Zhao and Hongtao 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 Expression Recognition,” ICNN&B2005, vol. 3, pp. 1970-1975.

 
 

Previous publications 

 

Neural networks and chaos: 

1.    Xiangjun Wu, Hui Wang, Hongtao Lu. Modified generalized projective synchronization of a new fractional-order hyperchaotic system and its application in secure communication. Nonlinear Analysis: Real World Applicationsv 13, n 3, p 1441-1450, June2012.SCI,IF 2.138

2.    Xiangjun Wu, Hongtao Lu. Outer synchronization of uncertain general complex delayed networks with adaptive coupling. Neurocomputingv 82, p 157-166, April 1, 2012.SCI,IF 1.429

3.    Wu Xiangjun Lu Hongtao. Generalized function projective (lag, anticipated and complete) synchronization between two different complex networks with nonidentical nodes. Communications in Nonlinear Science and Numerical Simulation, v 17, n 7, p 3005-3021, July 2012.

4.     Xiangjun Wu, Darong Lai, Hongtao Lu. Generalized synchronization of the fractional-order chaos in weighted complex dynamical networks with nonidentical nodes. Nonlinear Dynamics.SCI,IF 1.741

5.    Darong Lai, Xiangjun Wu, Hongtao Lu, Christine Nardini. Learning overlapping communities in complex networks via non-negative matrix factorization. International Journal of Modern Physics C, Vol. 22, No. 10 (2011) 1173-1190. SCI,IF 1.260

6.    Xiangjun Wu, Hongtao Lu. Cluster synchronization in the adaptive complex dynamical networks via a novel approach. Physics Letters A. 2011, 375(14): 1559-1565.SCI,IF 1.963

7.    Xiangjun Wu, Hui Wang, Hongtao Lu. Hyperchaotic secure communication via generalized function projective synchronization. Nonlinear Analysis: Real World Applications. 2011, 12(2): 1288-1299.SCIEI,IF 2.138

8.    Xiangjun Wu, Hongtao Lu. Generalized projective lag synchronization between different hyperchaotic systems with uncertain parameters. Nonlinear Dynamics. 2011, 66(1-2): 185-200.SCIEI,IF 1.741

9.    Xiangjun Wu, Hongtao Lu. Adaptive generalized function projective lag synchronization of different chaotic systems with fully uncertain parameters. Chaos Solitons & Fractals. 2011, 44(10): 802-810.SCI,IF 1.267

10.    Wu X, Lu H. “Generalized projective synchronization between two different general complex dynamical networks with delayed coupling”. Physics Letters A, Volume 374, Issue 38, 2010, Pages 3932-3941.

11.    Wu X, Lu H. “Exponential synchronization of weighted general delay coupled and non-delay coupled dynamical networks”. Computers& Mathematics with Applications, Volume 60, Issue 8, 2010, Pages 2476-2487.

12.    Wu X, Lu H. “Outer synchronization between two different fractional-order general complex dynamical networks”. Chinese Physics B, Volume 19, Issue 7, 2010, Pages 070511.

13.    Xiangjun Wu, Hongtao Lu, Shilei Shen, Synchronization of a new fractional-order hyperchaotic system. Physics Letters A, 373(2009)2329-2337.

14.    Hongtao Lu, Guanrong Chen, “Global synchronization in an array of linearly coupled delayed neural networks with an arbitrary coupling matrix,” International Journal of Bifurcation and Chaos, vol.16, no.11, pp.3357-3368, 2006.

15.    Hongtao Lu and Shun-ichi Amari, “Global exponential stability of multi-time scale competitive neural networks with nonsmooth functions,” IEEE Transactions on Neural Networks, vol.17, no.5, pp.1152-1164, Sep. 2006.

16.    Hongtao Lu and C.A. Leeuven, “Synchronization of chaotic neural networks via output or state coupling,” Chaos, Solitons and Fractals, 30(2006)166-176.

17.    Hongtao Lu and Guanrong Chen, “Global exponential convergence of multi-time scale neural networks,” IEEE Transactions on Circuits and Systems II, vol.52, no.11, pp.761-765, November, 2005.

18.    Hongtao Lu, “Global exponential stability analysis of Cohen-Grossberg neural networks,” IEEE Transactions on Circuits and Systems II, vol.52, no.9, pp.476-479, August, 2005.

19.    Hongtao Lu“Comments on ‘A Generalized LMI-Based Approach to the Global Asymptotic Stability of Delayed Cellular Neural Networks’”IEEE Transactions on Neural Networks, vol.16, no.3, pp.778-779, May, 2005.

20.    Hongtao Lu, Ruiming Shen and Fulai Chung, “Global exponential convergence of Cohen-Grossberg neural networks with time delays,” IEEE Transactions on Neural Networks, vol.16, no.6, pp.1694-1696, November, 2005.

21.    Hongtao Lu, Ruiming Shen, and Fu-Lai Chung, “Absolute exponential stability of a class of recurrent neural networks with multiple and variable delays,” Theoretical Computer Science, 344(2005)103-119.

22.    HongtaoLu and XinzhenYuLocal bifurcations in delayed chaos anticontrol systems, Journal of Computational and Applied Mathematics, 181(2005)188-199.

23.    Hongtao Lu and Zhenya He, “Global exponential stability of delayed competitive neural networks with different time scales,” Neural Networks, 18(2005)243-250.

24.    Hongtao Lu, Absolute exponential stability analysis of delayed neural networks, Physics Letters A, 336(2005)133-140.

25.    Hongtao Lu, Zhenya He and Fulai Chung Some sufficient conditions for exponential stability of delayed neural networks. Neural Networks, vol.17, pp.537-544, 2004. 

26.    Hongtao Lu and K. S. Tang, Chaotic Phase Shift Keying in Delayed Chaotic Anticontrol Systems,  International Journal of Bifurcation and Chaosvol.12, no.5, 1017-1028, 2002.

27.    Hongtao Lu, Chaotic attractors in delayed neural networks. Physics Letters A,  2982002109-116.

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 nonlinear continuous-time neural networks with delays. Neural Networks, vol. 13, 1135-1143, 2000.

30.    Hongtao Lu, Yongbao He and Zhenya He, A chaotic generator: Analysis of the dynamic behaviour of a cellular 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 on Circuits and Systems, vol.43, no. 8, pp.700-702, 1996.

32.    Hongtao Lu, Zhenya He, Synchronization of chaotic systems based on system partition approaches. Physics Letters A,vol.219, pp.271-276, 1996.


  

Complex Networks:

1.    Darong Lai, Xiangjun Wu and Hongtao Lu, Learning Overlapping Communities in Complex Networks via Non-negative Matrix Factorization. International Journal of Modern Physics C, Vol. 22, No. 10 (2011) 1173-1190.

2.    Darong Lai, Xinyi Yang, Gang Wu, Yuanhua Liu and Christine Nardini, Inference of Gene Networks-application to Bifidobacterium, Bioinformatics, vol.27, No.2, pp. 232-237, 2011.

3.    Darong Lai, Christine Nardini and Hongtao Lu, Partitioning networks into communities by message passing, Physical Review E, vol.83, 016115, 2011.

4.    Darong Lai, Hongtao Lu and Christine Nardini, Enhanced modularity-based community detection by random walk network preprocessing, Physical Review E, vol.81, 066118, 2010.

5.    Darong Lai, Hongtao Lu and Christine Nardini, Extracting weights from edge directions to find commmunities in directed networks, Journal of Statistical Mechanics: Theory and Experiment, 2010, P06003.

6.    Darong Lai, Hongtao Lu and Christine Nardini, Finding communities in directed networks by PageRank random walk induced network embedding, Physica A: Statistical Mechanics and its Applications, vol. 389, pp. 2443-2454, 2010.

7.    Darong Lai, Hongtao Lu, Mario Lauria, Diego di Bernardo and Christine Nardini, MANIA: A gene network reverse algorithm for compounds mode-of-action and genes interactions inference, Advances in Complex Systems, vol. 13, issue 1, pp83-94, 2010 .

8.    Gang Yu, Xianpeng Wang and Hongtao Lu, Efficient routing strategy on scale-free network. Modern physics letters B, Vol. 23, No. 11 (2009)1377-1389.

9.    Xianpeng Wang, Gang Yu and Hongtao Lu,  A local information-based routing strategy on the scale-free network. Modern physics letters B, Vol. 23, No. 10 (2009)1291-1301.

10.    Darong Lai, Hongtao Lu, Indenification of community structure in complex networks using affinity propagation clustering method.  Modern physics letters B, Vol. 22, No. 16 (2008) 1547-1566 

11.    Xutao Wang, Guanrong Chen and Hongtao Lu,  A very fast algorithm for detecting community structures in complex networks.  Physica A, Vol. 384, Issue 2, pp. 667-67415 October 2007.

12.    Xutao Wang, Hongtao Lu, and Guanrong Chen,  The Modeling of Weighted Complex Networks.  Modern Physics Letters Bvol.21, No.16, pp.2813-2820, 2007. SCI

13.    Xuan Guo, Hongtao Lu, Traffic Congestion Analysis in Complex Networks Based on Various Routing Strategies.  Modern Physics Letters B Vol.21, No.15, pp.929-939, 2007. SCI 



Information Hiding:

1.    He, Zhongwei; Sun, Wei;  Lu Wei; Lu, Hongtao. Digital image splicing detection based on approximate run length. Pattern recognition letters, vol: 32, no: 12, pages:1591-1597   DOI: 10.1016/j.patrec.2011.05.013, 2011.

2.    Wei Lu, Wei Sun, Fu-Lai Chung and Hongtao Lu. Revealing digital fakery using multiresolution decomposition and higher order statistics. Engineering applications of artificial intelligence, vol.24, no.4, page. 666-672, JUN 2011.

3.    Wei Lu, Hongtao Lu and Fu-Lai Chung, “Feature based robust watermarking using image normalization”, Computers and Electrical Engineering,36(2010)2-18.

4.    Wei Lu, Wei Sun and Hongtao Lu, “Robust watermarking based on DWT and nonnegative matrix 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 Support Vector Machines. Computer Standard and Interface302008132-136.

7.    Wei Lu, Hongtao Lu and Fu-Lai Chung, “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-Lai Chung, “Robust digital image watermarking based on subsampling,” Applied Mathematics and Computation, vol. 181, no.2, pp.886-893, Oct., 2006.

9.    Wei Lu, Hongtao Lu and Fu-Lai Chung, “Feature based watermarking using template match,”  Applied mathematics and computation 177(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 Integrity Protection of XML Documents," International Journal of Computer Science and 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,” Pattern recognition, 38(2005)1321-1323.

13.    Zhao Qijun, Lu Hongtao, Jiang Xiaohua, “Web page watermarking for tamper-proof,” Journal of Shanghai 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,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E88-A, no.11, pp.3239-3240, 2005.

15.    Ruiming Shen, Yonggang Fu and Hongtao Lu, “A Novel Image Watermarking Scheme based on Support Vector Regression,” 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 watermarking scheme for image authentication,” Electronics Lettersvol.39, no.12, pp.898-900,2003.

17.    Y.Fu, R.Shen and H.Lu, “Watermarking scheme based on support vector machine for colour images,” Electronics Letters, vol.40, no.16, pp.986-9872004.

18.    Qiu Yunjie, Lu Hongtao, Deng Nan, Cai Nengbin. A robust image watermarking shceme based on template in LAB color space. Communications in Computer and Information Science, v 234 CCIS, PART 4, 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 watermarking schemes, Fifth International Conference on Information Assurance and Security(IAS2009), vol. 2, pp.326-329, August 18-20, Xi’an China, 2009.

21.    Peng Sun, Hongtao Lu, An efficient web page watermarking scheme. 2009 2nd IEEE International Conference on Computer Science and Information Technology(ICCSST2009), pp.163-167, 2009.

22.    Liu, Xiangyang, Lu, HongtaoFragile Watermarking Schemes for Tamperproof Web Pages. ISNN 2008, Part II, LNCS 5264, pp 552-559, 2008.

23.    Wei Lu, Wei Sun, Ji-wu Huang, Hongtao Lu, Digital image forensics using statistical features and neural network classifier. the Seventh International Conference on Machine Learning and Cybernetics, 20082831-2934.

24.    Wei Lu, Wei Sun, and Hongtao Lu, Blind Image Watermark Analysis Using Feature Fusion and Neural Network Classifie. International Symposium on Neural Networks 2008LNCS 5264237-242.

25.    Wei Lu and Hongtao LuContent Dependent Image Watermarking using Chaos and Robust Hash. 2007International Conference on Computational Intelligence and Security (CIS2007).

26.    Wei Lu, Hongtao Lu and Fu-lai Chung, “Robust image watermarking using 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 spectrum robust watermarking in DWT domain,” Proc. of the fourth international conference on 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 Network Detector”. ISNN2005, LNCS 3497, pp.801-806, 2005.

30.    Yonggang Fu, Ruiming Shen, Hongtao Lu and Xusheng Lei, “SVR-based oblivious 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 in Computer Science, 3174: 651-656 2004.

32.    Yonggang Fu, Ruimin Shen, Hongtao Lu, “Optimal watermark detection based 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


 

EEG Processing: 

1.    Jing-Nan Gu, Hong-Jun Liu, Hong-Tao Lu and Bao-Liang Lu, “An Integrated Hierarchical Gaussian Mixture Model to Estimate Vigilance Level Based on EEG Recordings,” ICONIP, Shanghai, China, 2011.

2.    Hongbin Yu, Hongtao Lu, Vigilance Estimation Based on Statistic Learning with One ICA Component of EEG Signal. ICONIP, Shanghai, China, 2011.

3.    Hong-Bin Yu, Hong-Tao Lu ,Tian Ouyang, Hong-Jun Liu, Bao-Liang Lu, “Vigilance Detection Based on Sparse Representation of EEG,” International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina, Sep., 2010.

4.    Tian Ouyang, Hong-Tao Lu, Bao-Liang Lu, “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 on Continuous Wavelet Transform of EEG Signals,” International Conference of Biomedical Engineering and Computer Science, Wuhan, China, 2010.

6.    Hongjun Liu, Qingsheng Ren, and Hongtao Lu, Estimating vigilance in driving simulation based on detection of light drowsiness. International conference on bioinformatics 2010, pp. 131-134Valencia, Spain, 2010.

7.    Hong-Jun Liu, Hong-Bin Yu, Qing-Sheng Ren, Hong-Tao Lu, “Estimate Vigilance Level in Driving Simulation Based on Sparse Representation,” 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 EEG signals,” Computer Communication Control and Automation, Taiwan, China, 2010.

Grants from government

1. Deep neural network compression and its applicationsNSFC2018-2021PI 

2. Diagnosis of bone cancer based on deep learningNSFC2019-2022member

3. Robot group intelligence interaction and optimal control under ubiquitous information manufacturing environmentsNSFC key projectmember

4. New theories and algorithms for big data representation and calculationKey fundamental project of Shanghai2017-2019PI

5. Low-rank Distance Metric Learning and its Applications.  (NSFC, 2013-2016, PI) 

6. Community Detection of Complex Networks based on Machine Learning (NSFC, 2009-2011,PI) 

7. Vigilance Estimation based on EEG and Video (863, 2008-2010, PI)


Grants from industry

1. Surveillance video online optimization techniques

2. Crowd estimation and localization techniques

3. Image and video captioning based on deep learning

4. Applications of deep learning in computer vision

5. OCR for receipt images


1.    Non-linear theory of neural networks and its applications on information hiding and pattern recognition. (Natural science award of Shanghai municipality, second class, 1st place)

2.    Synchronization, control and application of complex chaotic dynamic systems (Science and technology advancement award of Henan Province, second class, 2nd place)

3.    Anti-counterfeiting techniques of judicial digital images (Science and technology advancement award of Shanghai, Third class, 3rd place)

4.    Best paper award of CAISSE 2012

5.    Best paper award of ACCV 2009

6.    Among the most-cited researchers of China in Computer Science by Elsevier from 2014-2018.

7.    Selected as New Century Excellent Talent in 2005

8.    Selected as Down Program Scholar of Shanghai in 2003

PC members: AAAI, ISNN, IJCNNICONIPICIST…

Associative Editor: Signal collection and processing

Member of: Visual computation and cognitive, CCA biocybernetics and BME in China

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