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Faculty
Name: Mingsheng LONG
Title: Associate Professor
Post: PhD Supervisor
Email: mingsheng@tsinghua.edu.cn
Research Fields: Machine Learning, with special interest in transfer learning, deep learning, knowledge learning and their applications to artificial intelligence and industrial data software
Homepage: http://ise.thss.tsinghua.edu.cn/~mlong
Education
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
Jan. 2019 – Present, Associate Professor, School of Software, Tsinghua University
Jul. 2016 – Dec. 2018, 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
Academic Services
Associate Editor: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Journal Reviewer: Nature, JMLR, AIJ
Program Chair: NIPS Transfer Learning Workshop, ICCV TASK-CV Workshop
Area Chair: ICML, NIPS, ICLR, IJCAI, AAAI
Program Committee Member: CVPR, ICCV, KDD
Member, CCF Technical Committee on Artificial Intelligence and Pattern Recognition
Member, CAAI Technical Committee on Pattern Recognition
Honors and Awards
2020, Excellent Young Scholar, National Natural Science Foundation of China
2020, Rising Star in Science and Technology of Beijing
2020, CNKI Popular Dissertation Top 20 in China
2018, Technical Invention Award, China Ministry of Education (4th contributor)
2018, Teaching Award, Tsinghua University
2017, Service Award for International Cooperation, Tsinghua University
2016, Distinguished Dissertation Award, China Association for Artificial Intelligence (CAAI)
2014, Distinguished Dissertation Award, Tsinghua University
Academic Achievements
A complete list of publications can be found at my homepage: http://ise.thss.tsinghua.edu.cn/~mlong.
Five representative papers:
1. Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan. Learning Transferable Features with Deep Adaptation Networks. International Conference on Machine Learning (ICML), 2015. (Most Influential Papers of ICML, 2000+ Citations)
2. Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan. Conditional Adversarial Domain Adaptation. Neural Information Processing Systems (NIPS), 2018. (Most Influential Papers of NIPS, 600+ Citations)
3. Yuchen Zhang, Tianle Liu, Mingsheng Long*, Michael I. Jordan. Bridging Theory and Algorithm for Domain Adaptation. International Conference on Machine Learning (ICML), 2019. (The first margin theory of transfer learning)
4. Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan. Deep Transfer Learning with Joint Adaptation Networks. International Conference on Machine Learning (ICML), 2017. (Most Influential Papers of ICML, 1000+ Citations)
5. Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan. Unsupervised Domain Adaptation with Residual Transfer Networks. Neural Information Processing Systems (NIPS), 2016. (800+ Citations)
Teaching Activities
Deep Learning, for graduate, 2018 –
Machine Learning, for undergraduate, 2019 –
Introduction to Artificial Intelligence, for undergraduate, 2021 –
