个人资料：

姓名：徐宁
职称：讲师
学科专业：信息与通信工程(一级学科)/信号与信息处理(二级学科)
通讯地址：天津大学电气自动化与信息工程学院26教学楼D区
电子信箱：ningxu@tju.edu.cn
电话/传真：**

主要经历：
(1) 2019.07-至今 天津大学电气自动化与信息工程学院，信息与通信工程，讲师
(2) 2016.03-2017.03新加坡国立大学，计算机学院，博士联合培养
(3) 2013.09-2019.06天津大学电气自动化与信息工程学院，信息与通信工程，硕博连读
主要研究方向：
(1) 计算机视觉
(2) 机器学习
(3) 视觉自然语言描述
(4) 视觉关系识别
代表性论著、学术著作：
(1) Ning Xu, An-An Liu, Weizhi Nie, Yuting Su: Attention-in-Attention Networks for Surveillance Video Understanding in Internet of Things. IEEE Internet of Things Journal. 2018, 5(5): 3419-3429 (SCI)
(2) An-An Liu,Ning Xu, Weizhi Nie, Yuting Su, Yongkang Wong, Mohan S. Kankanhalli: Benchmarking a Multimodal and Multiview and Interactive Dataset for Human Action Recognition. IEEE Transactions on Cybernetics. 2017, 47(7): 1781-1794 (SCI)
(3) An-An Liu,Ning Xu*, Weizhi Nie, Yuting Su, Yong-Dong Zhang: Multi-Domain and Multi-Task Learning for Human Action Recognition. IEEE Transactions on Image Processing. 2019, 28(2): 853-867 (SCI)
(4) An-An Liu,Ning Xu, Yuting Su, Hong Lin, Tong Hao, Zhaoxuan Yang: Single/multi-view human action recognition via regularized multi-task learning. Neurocomputing. 2015, 151: 544-553 (SCI)
(5) Ning Xu, An-An Liu, Jing Liu, Weizhi Nie, Yuting Su: Scene graph captioner: Image captioning based on structural visual representation. Journal of Visual Communication and Image Representation. 2019, 58: 477-485 (SCI)
(6) An-An Liu,Ning Xu, Yongkang Wong, Junnan Li, Yuting Su, Mohan S. Kankanhalli: Hierarchical & multimodal video captioning: Discovering and transferring multimodal knowledge for vision to language. Computer Vision and Image Understanding. 2017, 163: 113-125 (SCI)
(7) An-An Liu,Ning Xu, Hanwang Zhang, Weizhi Nie, Yuting Su, Yongdong Zhang: Multi-Level Policy and Reward Reinforcement Learning for Image Captioning. International Joint Conference on Artificial Intelligence 2018: 821-827 (CCF-A)
(8) Ning Xu, An-An Liu, Weizhi Nie, Yongkang Wong, Fuwu Li, Yuting Su: Multi-modal & Multi-view & Interactive Benchmark Dataset for Human Action Recognition. ACM International Conference on Multimedia 2015: 1195-1198 (CCF-A)
主要学术成就、奖励及荣誉：
(1) ACM Multimedia 2016 Grand Challenge MSR Video to Language,排名第六（50个参赛队）
(2) TRECVID 2015国际顶级评测单项第一