您现在的位置是: 李长升

国家级高层次人才

姓名:李长升
所在学科:
职称:教授
联系电话:
E-mail:lcs@bit.edu.cn
通信地址:北京海淀区中关村南大街5号永利皇宫463cc

个人信息

        李长升,永利皇宫463cc教授,博士生导师,国家级青年人才,基金委联合基金会评专家。2008年于电子科技大学电子工程学院取得工学学士学位,2013年于中科院自动化所取得工学博士学位。在加入北京理工大学之前,先后在IBM研究院,阿里巴巴达摩院,以及电子科技大学计算机科学与工程学院工作。主要研究方向包括机器学习、数据挖掘、计算机视觉等。在IEEE TPAMI、TIP、TNNLS、TC等著名国际期刊以及AAAI、IJCAI、CVPR等著名国际会议发表论文近60篇,含中科院JCR-1区、CCF A论文30余篇。其中,以第一作者/通讯作者发表在例如T-PAMI等中科院JCR-1区或CCF A类文章20余篇。

        先后主持国家自然科学基金优秀青年科学基金、国家重点研发计划课题等纵向与横向项目10余项;参与国家自然科学基金重点项目2项。授权中国、美国、日本等国内外发明专利30余件。现担任多个国际顶级期刊和会议的审稿人,包括IEEE汇刊IEEE T-NNLS, T-KDE, T-C, T-MM, T-ECS, T-CSVT, T-II,以及中国计算机学会(CCF)A类会议CVPR,ICCV,ECCV,IJCAI,AAAI, NIPS, MM, UbiComP,MICCAI等。

  担任中国工程院工程科技知识中心专家、中宣部和科技部“宣传思想文化工作与大数据应用”工程论证专家、中国人工智能开源软件发展联盟专家委员会委员、首届太湖信用大数据创新应用大赛专家委员会委员。

  News: 每年计划招收博士生1人、硕士研究生3至4人,同时欢迎优秀的本科生加入实验室。(注:具有ACM程序设计竞赛、IEEE极限编程竞赛或者其它科技竞赛背景者将优先考虑)。



科研方向

  机器学习,包括深度学习,自空间学习、主动学习、多任务学习、模型压缩,元学习等;计算机视觉,包括视频行为识别与检测、场景理解等。

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].


承担科研情况

1. 国家自然科学基金委优青项目,大数据分析, 2022.01- 2024.12, 主持,在研

2. 国家重点研发计划,科技奥运互动发展与成果集成评估技术研究, 2021.08-2022.12, 课题负责人,在研

3. 国家自然科学基金委联合基金重点项目,大规模数据驱动的机器学习理论与方法,2021.01-2024.12, 主要参与人,在研

4. 国家自然科学基金委重点项目,面向领域大数据的事件知识图谱构建研究,2019.01-2022.12, 参与人,在研

5. 国家自然科学基金委青年项目,面向流式数据的在线自步多任务特征学习研究,2019.01-2021.12,主持,已结题

6. 华为委托项目,基于Python的机器学习分布式框架技术,2020.8-2022.2, 主持,已结题

7. 美团委托项目,道路环境中的行人精准感知,2020.10-2021.10,主持,已结题

8. 中电科29所委托项目,***小样本数据增强与目标识别技术, 2020.10-2022.4,主持,在研

9. 平安科技委托项目,医疗图像中的主动学习技术,2018.6-2019.6,主持,已结题


所获奖励

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