软件学院

School Of Software

Introduction:

Name: Mingsheng Long
Position:Assistant Professor
Email: longmingsheng@gmail.com, mingsheng@tsinghua.edu.cn
Address: Room 11-413, East Main Building, Tsinghua University
Homepage: http://ise.thss.tsinghua.edu.cn/~mlong


Education background:

Sep. 2008 – Jul. 2014, Ph.D., Department of Computer Science, Tsinghua University
Sep. 2004 – Jul. 2008, B.E., Department of Electrical Engineering, Tsinghua University


Experience:

Mar. 2017 – Present, Group Leader, Big Data Analysis Group, National Engineering Laboratory for Big Data System Software
Jul. 2016 – Present, Assistant Professor, School of Software, Tsinghua University
Sep. 2014 – Oct. 2015, Visiting Researcher, Department of Computer Science, University of California, Berkeley
Jul. 2014 – Jul. 2016, Postdoctoral Researcher, School of Software, Tsinghua University


Concurrent Academic:

Member of the ACM, IEEE, CCF, and CAAI
Program Committee Chair: NIPS Workshop on Transfer and Multi-Task Learning
Program Committee Member: ICML, NIPS, ACM KDD, ACM MM, IJCAI, ACM CIKM, etc.
Reviewer for International Journals: IEEE TPAMI, IEEE TKDE, IEEE TIP, IEEE TNNLS, ACM TKDD, ACM TIST, ACM TOMM, Artificial Intelligence, Machine Learning, Pattern Recognition, Information Sciences, etc.


Areas of Research Interests/ Research Projects:

Machine Learning, Deep Learning, Big Data Analysis


Honors And Awards:

2016, Distinguished Dissertation Award, China Association for Artificial Intelligence (CAAI)
2014, Distinguished Dissertation Award, Tsinghua University
2012, Best Paper Award Nominee, SIAM International Conference on Data Mining (SDM)


Academic Achievement:

Publications
More than 20 papers are published in peer-reviewed venues, including 18 papers published in top conferences and journals (CCF rank A) and cited by more than 600 in Google Scholar. Complete publications can be found in my homepage: http://ise.thss.tsinghua.edu.cn/~mlong

Selected Publications (*Corresponding Author):

[1] Yunbo Wang, Mingsheng Long*, Jianmin Wang, Philip S. Yu. Spatiotemporal Pyramid Network for Video Action Recognition. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (CVPR 2017)

[2] Yue Cao, Mingsheng Long*, Jianmin Wang, Shichen Liu. Deep Visual-Semantic Quantization for Efficient Image Retrieval. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (CVPR 2017)

[3] Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang. Transitive Hashing Network for Heterogeneous Multimedia Retrieval. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), 2017. (AAAI 2017) (The First Author is A Third-Year Undergraduate Student)

[4] Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan. Unsupervised Domain Adaptation with Residual Transfer Networks. In Proceedings of Advances in Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016. (NIPS 2016)

[5] Mingsheng Long, Yue Cao, Jianmin Wang, Philip S. Yu. Composite Correlation Quantization for Efficient Multimodal Retrieval. In Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Pisa, Italy, 2016. (SIGIR 2016)

[6] Yue Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang, Philip S. Yu. Deep Visual-Semantic Hashing for Cross-Modal Retrieval. In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Francisco, USA, 2016. (KDD 2016)

[7] Mingsheng Long, Jianmin Wang, Yue Cao, Jiaguang Sun, Philip S. Yu. Deep Learning of Transferable Representation for Scalable Domain Adaptation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(8):2027-2040, 2016. (TKDE 2016)

[8] Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan. Learning Transferable Features with Deep Adaptation Networks. In Proceedings of International Conference on Machine Learning (ICML), Lille, France, 2015. (ICML 2015)

[9] Mingsheng Long, Jianmin Wang, Jiaguang Sun, Philip S. Yu. Domain Invariant Transfer Kernel Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(6):1519-1532, 2015. (TKDE 2015)

[10] Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang. Transfer Learning with Graph Co-Regularization. IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(7):1805-1818, 2014. (TKDE 2014)

[11] Mingsheng Long, Jianmin Wang, Guiguang Ding, Sinno Jialin Pan, Philip S. Yu. Adaptation Regularization: A General Framework for Transfer Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(5):1076-1089, 2014. (TKDE 2014) (Top 2% Highly Cited Paper)

[12] Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu. Transfer Joint Matching for Unsupervised Domain Adaptation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. (CVPR 2014)

[13] Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu. Transfer Feature Learning with Joint Distribution Adaptation. In Proceedings of IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 2013. (ICCV 2013)

[14] Mingsheng Long, Guiguang Ding, Jianmin Wang, Jiaguang Sun, Philip S. Yu. Transfer Sparse Coding for Robust Image Representation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013. (CVPR 2013)

[15] Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei Cheng, Xiang Zhang, Wei Wang. Dual Transfer Learning. In Proceedings of SIAM International Conference on Data Mining (SDM), Anaheim, USA, 2012. (SDM 2012) (Best Paper Award Nominee)