Name: Li Changsheng
Discipline:
Title: Professor, Doctoral Supervisor, National Outstanding Youth
Contact number:
E-mail: lcs@bit.edu.cn
Address: School of Computer Science, No.5 Zhongguancun South Street, Haidian District, Beijing Personal Information
Li Changsheng, professor of School of Computer Science, Beijing Institute of Technology, doctoral supervisor, national young talent, Foundation Committee joint foundation evaluation expert. He received his Bachelor of Engineering degree from the School of Electronic Engineering, University of Electronic Science and Technology of China in 2008, and his Doctor of Engineering degree from the Institute of Automation, Chinese Academy of Sciences in 2013. Before joining the Beijing Institute of Technology, he worked at IBM Research, Alibaba Damo Institute, and the School of Computer Science and Engineering at the University of Electronic Science and Technology of China. His research interests include machine learning, data mining, computer vision, etc. He has published nearly 60 papers in IEEE TPAMI, TIP, TNNLS, TC and other famous international journals and AAAI, IJCAI, CVPR and other famous international conferences, including more than 30 papers in JCR-1 District of the Chinese Academy of Sciences and CCFA. Among them, as the first author/corresponding author, he published more than 20 articles in the JCR-1 area of Chinese Academy of Sciences or CCF class A, such as T-PAMI.
He has presided over more than 10 vertical and horizontal projects such as the National Natural Science Foundation Outstanding Youth Science Fund and the National key research and development program. Participated in 2 key projects of the National Natural Science Foundation. More than 30 invention patents were authorized from China, the United States, Japan and other domestic and foreign countries. He is currently A reviewer for several top international journals and conferences, including IEEE Transactions IEEE T-NNLS, T-KDE, T-C, T-MM, T-ECS, T-CSVT, T-II, and the China Computer Society (CCF) Class A conference CVPR, ICCV, ECCV, IJCAI, CVPR, ICCV, ECCV, and IJCAI. AAAI, NIPS, MM, UbiComP, MICCAI, etc.
He served as an expert of the Engineering Science and Technology Knowledge Center of the Chinese Academy of Engineering, an engineering demonstration expert of the Propaganda Department and the Ministry of Science and Technology of the "Propaganda Ideological and Cultural work and big data application", a member of the expert committee of the China Artificial Intelligence Open Source Software Development Alliance, and a member of the expert committee of the first Taihu Credit Big Data Innovation Application Competition.
News: We plan to recruit 1 doctoral student and 3 to 4 master students every year, and welcome excellent undergraduates to join the laboratory. (Note: Background in ACM Programming Competition, IEEE Extreme Programming Competition, or other technical competitions will be preferred).

Research Direction
Machine learning, including deep learning, self-spatial learning, active learning, multi-task learning, model compression, meta-learning, etc. Computer vision, including video behavior recognition and detection, scene understanding, etc.

Personal Information
Li Changsheng, professor of School of Computer Science, Beijing Institute of Technology, doctoral supervisor, national young talent, Foundation Committee joint foundation evaluation expert. He received his Bachelor of Engineering degree from the School of Electronic Engineering, University of Electronic Science and Technology of China in 2008, and his Doctor of Engineering degree from the Institute of Automation, Chinese Academy of Sciences in 2013. Before joining the Beijing Institute of Technology, he worked at IBM Research, Alibaba Damo Institute, and the School of Computer Science and Engineering at the University of Electronic Science and Technology of China. His research interests include machine learning, data mining, computer vision, etc. He has published nearly 60 papers in IEEE TPAMI, TIP, TNNLS, TC and other famous international journals and AAAI, IJCAI, CVPR and other famous international conferences, including more than 30 papers in JCR-1 District of the Chinese Academy of Sciences and CCFA. Among them, as the first author/corresponding author, he published more than 20 articles in the JCR-1 area of Chinese Academy of Sciences or CCF class A, such as T-PAMI.
He has presided over more than 10 vertical and horizontal projects such as the National Natural Science Foundation Outstanding Youth Science Fund and the National key research and development program. Participated in 2 key projects of the National Natural Science Foundation. More than 30 invention patents were authorized from China, the United States, Japan and other domestic and foreign countries. He is currently A reviewer for several top international journals and conferences, including IEEE Transactions IEEE T-NNLS, T-KDE, T-C, T-MM, T-ECS, T-CSVT, T-II, and the China Computer Society (CCF) Class A conference CVPR, ICCV, ECCV, IJCAI, CVPR, ICCV, ECCV, and IJCAI. AAAI, NIPS, MM, UbiComP, MICCAI, etc.
He served as an expert of the Engineering Science and Technology Knowledge Center of the Chinese Academy of Engineering, an engineering demonstration expert of the Propaganda Department and the Ministry of Science and Technology of the "Propaganda Ideological and Cultural work and big data application", a member of the expert committee of the China Artificial Intelligence Open Source Software Development Alliance, and a member of the expert committee of the first Taihu Credit Big Data Innovation Application Competition.
News: We plan to recruit 1 doctoral student and 3 to 4 master students every year, and welcome excellent undergraduates to join the laboratory. (Note: Background in ACM Programming Competition, IEEE Extreme Programming Competition, or other technical competitions will be preferred).

Personal Information
Li Changsheng, professor of School of Computer Science, Beijing Institute of Technology, doctoral supervisor, national young talent, Foundation Committee joint foundation evaluation expert. He received his Bachelor of Engineering degree from the School of Electronic Engineering, University of Electronic Science and Technology of China in 2008, and his Doctor of Engineering degree from the Institute of Automation, Chinese Academy of Sciences in 2013. Before joining the Beijing Institute of Technology, he worked at IBM Research, Alibaba Damo Institute, and the School of Computer Science and Engineering at the University of Electronic Science and Technology of China. His research interests include machine learning, data mining, computer vision, etc. He has published nearly 60 papers in IEEE TPAMI, TIP, TNNLS, TC and other famous international journals and AAAI, IJCAI, CVPR and other famous international conferences, including more than 30 papers in JCR-1 District of the Chinese Academy of Sciences and CCFA. Among them, as the first author/corresponding author, he published more than 20 articles in the JCR-1 area of Chinese Academy of Sciences or CCF class A, such as T-PAMI.
He has presided over more than 10 vertical and horizontal projects such as the National Natural Science Foundation Outstanding Youth Science Fund and the National key research and development program. Participated in 2 key projects of the National Natural Science Foundation. More than 30 invention patents were authorized from China, the United States, Japan and other domestic and foreign countries. He is currently A reviewer for several top international journals and conferences, including IEEE Transactions IEEE T-NNLS, T-KDE, T-C, T-MM, T-ECS, T-CSVT, T-II, and the China Computer Society (CCF) Class A conference CVPR, ICCV, ECCV, IJCAI, CVPR, ICCV, ECCV, and IJCAI. AAAI, NIPS, MM, UbiComP, MICCAI, etc.
He served as an expert of the Engineering Science and Technology Knowledge Center of the Chinese Academy of Engineering, an engineering demonstration expert of the Propaganda Department and the Ministry of Science and Technology of the "Propaganda Ideological and Cultural work and big data application", a member of the expert committee of the China Artificial Intelligence Open Source Software Development Alliance, and a member of the expert committee of the first Taihu Credit Big Data Innovation Application Competition.
News: We plan to recruit 1 doctoral student and 3 to 4 master students every year, and welcome excellent undergraduates to join the laboratory. (Note: Background in ACM Programming Competition, IEEE Extreme Programming Competition, or other technical competitions will be preferred).

代表性学术成果
1. Changsheng Li, Handong Ma, Ye Yuan, Guoren Wang, Dong Xu, Structure Guided Deep Neural Network for Unsupervised Active Learning, IEEE Transactions on Image Processing (TIP), 2022, [CCF A].
2. Changsheng Li, Rongqing Li, Ye Yuan, Guoren Wang, Dong Xu, Deep Unsupervised Active Learning via Matrix Sketching, IEEE Transactions on Image Processing (TIP), 2021, [CCF A].
3. Changsheng Li, Chen Yang, Bo Liu, Ye Yuan, Guoren Wang, LRSC: Learning Representations for Subspace Clustering, AAAI Conference on Artificial Intelligence (AAAI- 21), 2021, [CCF A类].
4. Changsheng Li, Kaihang Mao, Lingyan Liang, Dongchun Ren, Wei Zhang, Ye Yuan, Guoren Wang, Unsupervised Active Learning via Subspace Learning, AAAI Conference on Artificial Intelligence (AAAI-21), 2021, [CCF A类]
5. Changsheng Li, Chen Yang, Lingyan Liang, Ye Yuan, Guoren Wang，On Robust Grouping Active Learning, IEEE Transactions on Emerging Topics in Computational Intelligence, 2020.
6. Changsheng Li; Handong Ma; Zhao Kang; Ye Yuan; Xiao-Yu Zhang, Guoren Wang*, On Deep Unsupervised Active Learning, International Joint Conferences on Artificial Intelligence (IJCAI), 2020. [CCF A类]
7. Xiao-Yu Zhang#, Changsheng Li#, Haichao Shi*, Xiaobin Zhu, Peng Li, Jing Dong, AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization, To Appear in IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020, [中科院JCR-1区].
8. Changsheng Li, Chong Liu, Lixin Duan*, Peng Gao, Kai Zheng, Reconstruction regularized deep metric learning for multi-label image classification, online, IEEE transactions on neural networks and learning systems (TNNLS), 2019, [中科院JCR-1区].
9. Changsheng Li, Xiangfeng Wang, Weishan Dong, Junchi Yan, Qingshan Liu, Hongyuan Zha, Joint Active Learning with Feature Selection via CUR Matrix Decomposition, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019，[中科院JCR-1区].
10. Changsheng Li*, Fan Wei, Weishan Dong, Qingshan Liu*, Xiangfeng Wang, Xin Zhang, Dynamic Structure Embedded Online Multiple-Output Regression for Streaming Data, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019，[中科院JCR-1区].
11. Changsheng Li, Fan Wei, Junchi Yan, Xiaoyu Zhang, Qingshan Liu, Hongyuan Zha, A Self-Paced Regularization Framework for Multilabel Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018, [中科院JCR-1区].
12. Changsheng Li, Junchi Yan*, Fan Wei, Weishan Dong, Qingshan Liu, Hongyuan Zha, Self-paced Multi-task Learning, The 31th AAAI Conference on Artificial Intelligence (AAAI-17), 2017, [CCF A类].
13. Changsheng Li, Fan Wei, Weishan Dong, Xiangfeng Wang, Junchi Yan, Xiaobin Zhu, Qingshan Liu, Xin Zhang, Spatially Regularized Streaming Sensor Selection, The 30th AAAI Conference on Artificial Intelligence (AAAI-16), 2016, [CCF A类].
14. Changsheng Li, Qingshan Liu, Weishan Dong, Fan Wei, Xin Zhang, Lin Yang, Max-Margin based Discriminative Feature Learning, IEEE Trans. on Neural Networks and Learning Systems, 2016, [中科院JCR-1区].
15. Changsheng Li, Qingshan Liu, Weishan Dong, Xiaobin Zhu, Jing Liu, Hanqing Lu, Human Age Estimation Based on Locality and Ordinal Information, IEEE Transaction on Cybernetics (TC), 2015, [中科院JCR-1区].
16. Changsheng Li, Qingshan Liu, Jing Liu, Hanqing Lu, Ordinal Distance Metric Learning for Image Ranking, IEEE Transaction on Neural Network and Learning Systems (TNNLS), 2015, [中科院JCR-1区].
17. Changsheng Li, Qingshan Liu, Jing Liu, Hanqing Lu, Learning ordinal discriminative features for age estimation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2570-2577, 2012, [CCF A类].
所获奖励