姓名：李长升
所在学科：
职称：准聘教授
联系电话：
E-mail：lcs@bit.edu.cn
通信地址：
个人信息 　　李长升，北京理工大学计算机学院准聘教授，博士生导师。分别获电子科技大学工学学士和中科院自动化所工学博士。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。在上述相关领域，近几年共发表国际期刊和会议50余篇，含中科院JCR-1区、CCF A论文26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17篇。
　　近五年，共主持包含国家自然科学基金在内的6项科研项目，主持项目总经费近900万人民币。在IBM工作期间，先后获得IBM Accomplishment Award，IBM Research & Division Award等。拥有9项美国专利授权，9项美国专利申请。 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等。
　　担任中宣部和科技部“宣传思想文化工作与大数据应用”工程论证专家、首届太湖信用大数据创新应用大赛专家委员会委员、中国人工智能开源软件发展联盟专家委员会委员。
　　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. 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], (# equally contributed).
　　2. Xiao-Yu Zhang, Haichao Shi, Changsheng Li*, Peng Li, Multi-instance Multi-label Action Recognition and Localization Based on Spatio-Temporal Pre-trimming for Untrimmed Videos, AAAI Conference on Artificial Intelligence (AAAI-20), 2020, [CCF A类](* corresponding author).
　　3. Ge Li, Changsheng Li*, Chan Zeng, Peng Gao, Guotong Xie, Region Focus Network for Joint Optic Disc and Cup Segmentation, AAAI Conference on Artificial Intelligence (AAAI-20), 2020, [CCF A类], (* corresponding author).
　　4. 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].
　　5. Xiao-Yu Zhang, Haichao Shi, Changsheng Li*, Kai Zheng, Xiaobin Zhu, Lixin Duan, Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision, AAAI Conference on Artificial Intelligence (AAAI), 2019, [CCF A类], (* corresponding author).
　　6. 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].
　　7. 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].
　　8. 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].
　　9. Junchi Yan, Xin Liu, Liangliang Shi, Changsheng Li*, Hongyuan Zha, Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), 2018, [CCF A类], (* corresponding author).
　　10. Weishan Dong, Ting Yuan, Kai Yang, Changsheng Li*, Shilei Zhang, Autoencoder Regularized Network For Driving Style Representation Learning, International Joint Conference on Artificial Intelligence (IJCAI), 2017, [CCF A类], (* corresponding author).
　　11. 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].
　　12. 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].
　　13. 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].
　　14. 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].
　　15. 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].
　　16. 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].

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