姓名：龙明盛
职务：副教授
邮件：longmingsheng@gmail.com, mingsheng@tsinghua.edu.cn
地址：清华大学东配楼11区413室
主页：http://ise.thss.tsinghua.edu.cn/~mlong

教育背景 2008年9月至2014年7月，清华大学计算机系，博士
2004年9月至2008年7月，清华大学电机系，学士


工作履历 2019年1月至今，清华大学软件学院，副教授
2017年3月至今，大数据系统软件国家工程实验室，机器学习研究组组长
2016年7月至2018年12月，清华大学软件学院，助理教授
2014年9月至2015年10月，加州大学伯克利分校计算机系，访问研究员
2014年7月至2016年7月，清华大学软件学院，博士后

学术兼职 ACM会员，IEEE会员，CCF会员，CAAI会员
国际会议联合主席：NIPS Transfer Learning Workshop，ICCV TASK-CV Workshop
国际会议领域主席：ICLR
国际会议高级程序委员会委员：IJCAI，AAAI
国际会议程序委员会委员：ICML，NIPS，KDD，CVPR，ICCV等
国际期刊审稿人：AIJ，JMLR，IJCV，TPAMI，TKDE，TIP，TNNLS等

研究领域 机器学习，深度学习，迁移学习，大数据分析
奖励与荣誉 2018年，教育部技术发明一等奖（第四完成人）
2018年，清华大学教学优秀奖
2017年，清华大学国际合作与交流暨港澳台工作优秀工作者
2016年，中国人工智能学会优秀博士学位论文
2014年，清华大学优秀博士学位论文
2012年，SIAM SDM国际数据挖掘会议最佳论文提名

学术成果 发表学术论文50余篇，其中第一/通讯作者CCF A类长文45篇，谷歌学术引用超过3600次，主要科研成果详见个人主页：http://ise.thss.tsinghua.edu.cn/~mlong
期刊论文：
[1] Mingsheng Long, Yue Cao, Zhangjie Cao, Jianmin Wang, Michael I. Jordan. Transferable Representation Learning with Deep Adaptation Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
[2] 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.
[3] 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.
[4] 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.
[5] 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. (1%高引论文)
会议论文 (*为通讯作者)：
[1] Xinyang Chen, Sinan Wang, Bo Fu, Mingsheng Long*, Jianmin Wang. Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning. Neural Information Processing Systems (NIPS), 2019.
[2] Ximei Wang, Ying Jin, Mingsheng Long*, Jianmin Wang, Michael I. Jordan. Transferable Normalization: Towards Improving Transferability of Deep Neural Networks. Neural Information Processing Systems (NIPS), 2019.
[3] Yuchen Zhang, Tianle Liu, Mingsheng Long*, Michael I. Jordan. Bridging Theory and Algorithm for Domain Adaptation. International Conference on Machine Learning (ICML), 2019.
[4] Kaichao You, Ximei Wang, Mingsheng Long*, Michael I. Jordan. Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation. International Conference on Machine Learning (ICML), 2019.
[5] Hong Liu, Mingsheng Long*, Jianmin Wang, Michael I. Jordan. Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers. International Conference on Machine Learning (ICML), 2019.
[6] Xinyang Chen, Sinan Wang, Mingsheng Long*, Jianmin Wang. Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation. International Conference on Machine Learning (ICML), 2019.
[7] Universal Domain Adaptation. Kaichao You, Mingsheng Long*, Zhangjie Cao, Jianmin Wang, Michael I. Jordan. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[8] Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long*, Jianmin Wang, Philip S. Yu. Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[9] Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, Li Fei-Fei. Eidetic 3D LSTM: A Model for Video Prediction and Beyond. International Conference on Learning Representations (ICLR), 2019.
[10] Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan. Conditional Adversarial Domain Adaptation. Neural Information Processing Systems (NIPS), 2018.
[11] Shichen Liu, Mingsheng Long*, Jianmin Wang, Michael I. Jordan. Generalized Zero-Shot Learning with Deep Calibration Network. Neural Information Processing Systems (NIPS), 2018.
[12] Yunbo Wang, Zhifeng Gao, Mingsheng Long*, Jianmin Wang, Philip S. Yu. PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning. International Conference on Machine Learning (ICML), 2018.
[13] Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Michael I. Jordan. Partial Transfer Learning with Selective Adversarial Networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[14] Yue Cao, Mingsheng Long*, Bin Liu, Jianmin Wang. Deep Cauchy Hashing for Hamming Space Retrieval. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[15] Yunbo Wang, Mingsheng Long*, Jianmin Wang, Zhifeng Gao, Philip S. Yu. PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs. Neural Information Processing Systems (NIPS), 2017.
[16] Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu. Learning Multiple Tasks with Multilinear Relationship Networks. Neural Information Processing Systems (NIPS), 2017.
[17] Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu. HashNet: Deep Learning to Hash by Continuation. IEEE International Conference on Computer Vision (ICCV), 2017.
[18] Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan. Deep Transfer Learning with Joint Adaptation Networks. International Conference on Machine Learning (ICML), 2017.
[19] Yunbo Wang, Mingsheng Long*, Jianmin Wang, Philip S. Yu. Spatiotemporal Pyramid Network for Video Action Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[20] Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan. Unsupervised Domain Adaptation with Residual Transfer Networks. Neural Information Processing Systems (NIPS), 2016.
[21] Yue Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang, Philip S. Yu. Deep Visual-Semantic Hashing for Cross-Modal Retrieval. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016.
[22] Han Zhu, Mingsheng Long*, Jianmin Wang, Yue Cao. Deep Hashing Network for Efficient Similarity Retrieval. AAAI Conference on Artificial Intelligence (AAAI), 2016.
[23] Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan. Learning Transferable Features with Deep Adaptation Networks. International Conference on Machine Learning (ICML), 2015. (谷歌引用900余次)
[24] Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu. Transfer Feature Learning with Joint Distribution Adaptation. IEEE International Conference on Computer Vision (ICCV), 2013.
[25] 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. (最佳论文提名)