Biography

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I am an assistant professor and Ph.D supervisor in the School of Software, Tsinghua University. My research interests include machine learning and big data, with specific focus on deep learning, transfer learning, and scalable machine learning methods, systems, and applications.

I am leading the Machine Learning Group in the National Engineering Laboratory for Big Data Systems. I am looking for highly motivated graduate or undergraduate students to work on machine learning and big data analysis. Please send me your CV if you are interested.

Research Interests

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• Machine Learning, Deep Learning, Transfer Learning, Big Data Analysis

Education

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• Ph.D. in Computer Science, 2008-2014
  Department of Computer Science and Technology, Tsinghua University, Beijing, China
  Advisor: Prof. Jianmin Wang

• B.E. in Electrical Engineering, 2004-2008
  Department of Electrical Engineering, Tsinghua University, Beijing, China

Research Experience

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• Visiting Researcher, 2014-2015
  AMPLab, UC Berkeley
  Advisor: Prof. Michael I. Jordan

• Postdoc Researcher, 2014-2016
  School of Software, Tsinghua University, Beijing, China
  Advisor: Prof. Jianmin Wang

Publications [DBLP] [Google Scholar]

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Journal Articles

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

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

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

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

Conference Proceedings

1. PredRNN: Recurrent Neural Networks for Video Prediction using Spatiotemporal LSTMs
   Yunbo Wang, Mingsheng Long*, Jianmin Wang, Zhifeng Gao, Philip S. Yu
   Neural Information Processing Systems (NIPS), 2017 (Accepted)

2. Learning Multiple Tasks with Deep Relationship Networks
   Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu
   Neural Information Processing Systems (NIPS), 2017 (Accepted)

3. HashNet: Deep Learning to Hash by Continuation
   Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
   IEEE International Conference on Computer Vision (ICCV), 2017 [PDF] [Code@Github]

4. Correlation Hashing Network for Efficient Cross-Modal Retrieval
   Yue Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
   British Machine Vision Conference (BMVC), 2017 [PDF]

5. Deep Transfer Learning with Joint Adaptation Networks
   Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan
   International Conference on Machine Learning (ICML), 2017 [PDF] [Slides] [Poster] [Code@Github]

6. Spatiotemporal Pyramid Network for Video Action Recognition
   Yunbo Wang, Mingsheng Long*, Jianmin Wang, Philip S. Yu
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 [PDF] [Slides] [Code@Github]

7. Deep Visual-Semantic Quantization for Efficient Image Retrieval
   Yue Cao, Mingsheng Long*, Jianmin Wang, Shichen Liu
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 [PDF] [Code@Github]

8. Transitive Hashing Network for Heterogeneous Multimedia Retrieval
   Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang
   AAAI Conference on Artificial Intelligence (AAAI), 2017 [PDF]

9. Collective Deep Quantization for Efficient Cross-Modal Retrieval
   Yue Cao, Mingsheng Long*, Jianmin Wang, Shichen Liu
   AAAI Conference on Artificial Intelligence (AAAI), 2017 [PDF] [Code@Github]

10. Unsupervised Domain Adaptation with Residual Transfer Networks
    Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan
    Neural Information Processing Systems (NIPS), 2016 [PDF] [Poster] [Code@Github]

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

12. Composite Correlation Quantization for Efficient Multimodal Retrieval
    Mingsheng Long, Yue Cao, Jianmin Wang, Philip S. Yu
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2016 [PDF] [Slides] [Code]

13. Correlation Autoencoder Hashing for Supervised Cross-Modal Search
    Yue Cao, Mingsheng Long*, Jianmin Wang, Han Zhu
    ACM International Conference on Multimedia Retrieval (ICMR), 2016

14. Deep Quantization Network for Efficient Image Retrieval
    Yue Cao, Mingsheng Long*, Jianmin Wang, Han Zhu, Qingfu Wen
    AAAI Conference on Artificial Intelligence (AAAI), 2016 [PDF] [Slides]

15. Deep Hashing Network for Efficient Similarity Retrieval
    Han Zhu, Mingsheng Long*, Jianmin Wang, Yue Cao
    AAAI Conference on Artificial Intelligence (AAAI), 2016 [PDF] [Code@Github]

16. Learning Transferable Features with Deep Adaptation Networks
    Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan
    International Conference on Machine Learning (ICML), 2015 [PDF] [Slides] [Poster] [Code@Github]

17. Local Hybrid Coding for Image Classification
    Wu Xiang, Jianmin Wang, Mingsheng Long
    International Conference on Pattern Recognition (ICPR), 2014
    

18. Inherent Replica Inconsistency in Cassandra
    Xiangdong Huang, Jianmin Wang, Jian Bai, Guiguang Ding, Mingsheng Long
    International Congress on Big Data (BigData), 2014
    

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

20. Transfer Feature Learning with Joint Distribution Adaptation
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu
    IEEE International Conference on Computer Vision (ICCV), 2013 [PDF] [Code]

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

22. Twin Bridge Transfer Learning for Sparse Collaborative Filtering
    Jiangfeng Shi, Mingsheng Long, Qiang Liu, Guiguang Ding, Jianmin Wang
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2013

23. Transfer Learning with Graph Co-Regularization
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang
    AAAI Conference on Artificial Intelligence (AAAI), 2012 [PDF] [Code]

24. Topic Correlation Analysis for Cross-Domain Text Classification
    Lianghao Li, Xiaoming Jin, Mingsheng Long
    AAAI Conference on Artificial Intelligence (AAAI), 2012 [PDF] [Code]

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

26. Transfer Learning via Cluster Correspondence Inference
    Mingsheng Long, Wei Cheng, Xiaoming Jin, Jianmin Wang, Dou Shen
    IEEE International Conference on Data Mining (ICDM), 2010 (Short Paper)

Preprints & Technical Reports

1. Domain Adaptation with Randomized Multilinear Adversarial Networks
   Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan, 2017 [arXiv]

2. Partial Transfer Learning with Selective Adversarial Networks
   Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Michael I. Jordan, 2017 [arXiv]

Honors and Awards

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• Distinguished Dissertation Award, China Association for Artificial Intelligence (CAAI), 2016
• Distinguished Dissertation Award Nominee, China Computer Federation (CCF), 2014
• Tsinghua University Outstanding Ph.D. Graduate, 2014
• Beijing Municipal Government Award for Outstanding Ph.D. Graduates, 2014
• Academic Rising Star, School of Software, Tsinghua University, 2014
• Zhong Shi-Mo Outstanding Graduate Scholarship, Tsinghua University, 2013
• Intel Fellowship, Tsinghua University, 2012
• Nominee of Best Paper Award, SIAM SDM, 2012
• Outstanding Contribution Award, Big Data Group, Tsinghua University, 2012
• Student Travel Award, IEEE ICDM, 2010

Professional Activities

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Organizer | Chair

• Transferring and Adapting Source Knowledge in Computer Vision Workshop and Challenge (TASK-CV), ICCV, 2017
• Transfer and Multi-Task Learning Workshop, NIPS, 2015

PC Member | Reviewer

• International Conference on Machine Learning (ICML) 2014, 2017
• Neural Information Processing Systems (NIPS) 2016, 2017
• IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018
• International Joint Conference on Artificial Intelligence (IJCAI) 2017
• AAAI Conference on Artificial Intelligence (AAAI) 2018
• ACM Multimedia Conference (MM) 2017
• Artificial Intelligence Journal (AIJ) 2016
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2016, 2017
• IEEE Transactions on Knowledge and Data Engineering (TKDE) 2014, 2015, 2016, 2017
• IEEE Transactions on Image Processing (TIP) 2014, 2015, 2016, 2017
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2016, 2017
• ACM Transactions on Knowedge Discovery from Data (TKDD) 2016
• ACM Transactions on Intelligent Systems and Technology (TIST) 2017
• ACM Transactions on Multimedia Computing, Communications and Applications (TOMM) 2014, 2015
• ACM Conference on Information and Knowledge Management (CIKM) 2017
• Machine Learning Journal (MLJ) 2016
• Data Mining and Knowledge Discovery (DMKD) 2012
• Information Science (IS) 2016
• Pattern Recognition (PR) 2016
• Neurocomputing 2016, 2012
• PLOS ONE 2015, 2016

Research Grants

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• Principal Investigator (PI), Spatiotemporal Deep Learning: Algorithms and Applications, 2018-2021
• Principal Investigator (PI), Safe Transfer Learning for Big Data Analytics, 2016-2018
• Principal Investigator (PI), Scalable Transfer Learning: Theory and Algorithms, 2015-2016

Teaching

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• Instructor: Deep Learning, 2018-Present
• Co-Instructor: Foundations of Big Data Systems (B), 2015-Present
• Co-Instructor: Foundations of Big Data Systems (A), 2016-Present
• Teaching Assistant: Introduction to Big Data Technology, 2014

Students

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Graduates Co-Supervised

• Class 2015: Yunbo Wang (THU PhD), Zhongyi Pei (THU PhD)
• Class 2014: Yue Cao (THU PhD), Han Zhu (THU->Alibaba, A-Star), Qiaoan Chen (THU->Tencent), Feng Li (Alibaba)
• Class 2013: Yateng Tang (THU->Tencent)
• Class 2012: Wei Li (THU->Google China)
• Class 2011: Wu Xiang (THU->Hulu), Hao Hu (THU->Google Mountain View)

Undergraduates

• Class 2016: Haixu Wu (THU->), Hongyu Zhu (THU->), Tianyang Wang (THU->)
• Class 2015: Ziping Sun (THU->), Chao Huang (THU->), Zhiyu Yao (THU->), Lijia Ma (THU->)
• Class 2014: Zhangjie Cao (THU->), Shichen Liu (THU->), Bin Liu (THU->)

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