Mingsheng Long

Assistant Professor, Ph.D Supervisor
School of Software, Tsinghua University

Machine Learning Group
National Engineering Laboratory for Big Data Systems

Curriculum Vitae
longmingsheng@gmail.com, mingsheng@tsinghua.edu.cn

Room 11-413, East Main Building, Tsinghua University, Beijing, China

Biography

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

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

Education

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

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]

Journal Articles

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]
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]
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]
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

HashNet: Deep Learning to Hash by Continuation
Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
IEEE International Conference on Computer Vision (ICCV), 2017 [arXiv]
Correlation Hashing Network for Efficient Cross-Modal Retrieval
Yue Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
British Machine Vision Conference (BMVC), 2017 [PDF]
Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan
International Conference on Machine Learning (ICML), 2017 [PDF] [Code@Github]
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] [Code]
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]
Transitive Hashing Network for Heterogeneous Multimedia Retrieval
Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang
AAAI Conference on Artificial Intelligence (AAAI), 2017 [PDF]
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]
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]
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]
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]
Correlation Autoencoder Hashing for Supervised Cross-Modal Search
Yue Cao, Mingsheng Long*, Jianmin Wang, Han Zhu
ACM International Conference on Multimedia Retrieval (ICMR), 2016
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]
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]
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]
Local Hybrid Coding for Image Classification
Wu Xiang, Jianmin Wang, Mingsheng Long
International Conference on Pattern Recognition (ICPR), 2014
Inherent Replica Inconsistency in Cassandra
Xiangdong Huang, Jianmin Wang, Jian Bai, Guiguang Ding, Mingsheng Long
International Congress on Big Data (BigData), 2014
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]
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]
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]
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
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]
Topic Correlation Analysis for Cross-Domain Text Classification
Lianghao Li, Xiaoming Jin, Mingsheng Long
AAAI Conference on Artificial Intelligence (AAAI), 2012 [PDF] [Code]
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)
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

Domain Adaptation with Randomized Multilinear Adversarial Networks
Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan, 2017 [arXiv]
Learning Multiple Tasks with Deep Relationship Networks
Mingsheng Long, Jianmin Wang, Philip S. Yu, 2017 [arXiv]

Honors and Awards

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

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
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

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

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