2010年8月至2016年1月：清华大学，博士

2014年11月至2015年6月：美国西北大学，访问学生

2006年9月至2010年7月：北京理工大学，学士

工作经历

2020年7月-至今，中国人民大学高瓴人工智能学院，准聘副教授

2019年10月-2020年1月，微软亚洲研究院，铸星计划访问研究员

2018年10月-2020年6月，中国科学院软件研究所，副研究员

2016年4月-2018年9月，中国科学院软件研究所，助理研究员

研究方向

序列距离学习：时序对齐、度量学习、序列特征变换、特征降维、最优传输、时序结构分析

受限条件下的机器学习：小样本学习、迁移学习、联邦学习、因果推理

计算机视觉应用：视频分类、动作识别、视觉与语义关联分析、序列预测

对学生的培养要求

对研究有兴趣；具备一定的编程能力；踏实、勤奋。欢迎对我研究方向感兴趣的同学与我联系。

科研项目

国家自然科学基金面上项目，批准号：61976206

项目名称：基于最优传输的序列距离学习理论和方法研究

国家自然科学基金青年科学基金项目，批准号：61603373

项目名称：基于最大化时序可分性的序列数据特征变换理论和方法研究

科研成果

1、期刊论文

— Bing Su and Ying Wu. “Learning Low-Dimensional Temporal Representations with Latent Alignments”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2019, accepted (CCF A)

— Bing Su and Gang Hua. “Order-preserving Optimal Transport for Distances between Sequences”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2019, 41(12), pp. 2961-2974. (CCF A)

— Bing Su, Xiaoqing Ding, Changsong Liu, and Ying Wu, "Heteroscedastic Max–Min Distance Analysis for Dimensionality Reduction", IEEE Trans. on Image Processing (TIP), 2018, 27(8), pp. 4052-4065. (CCF A)

— Bing Su, Xiaoqing Ding, Hao Wang, and Ying Wu, "Discriminative Dimensionality Reduction for Multi-Dimensional Sequences", IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2018, 40(1), pp. 77-91. (CCF A)

— Bing Su, Jiahuan Zhou, Xiaoqing Ding, and Ying Wu, "Unsupervised Hierarchical Dynamic Parsing and Encoding for Action Recognition ", IEEE Trans. on Image Processing (TIP), 2017, 26(12), pp. 5784-5799. (CCF A)

— Bing Su, Xiaoqing Ding, Changsong Liu, Hao Wang, and Ying Wu, "Discriminative Transformation for Multi-dimensional Temporal Sequences", IEEE Trans. on Image Processing (TIP), 2017, 26(7), pp. 3579-3593. (CCF A)

2、会议论文

— Jiahuan Zhou, Bing Su, and Ying Wu, "Online Joint Multi-Metric Adaptation from Frequent Sharing-Subset Mining for Person Re-Identification", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (CCF A)

— Bing Su, Jiahuan Zhou, and Ying Wu, "Order-Preserving Wasserstein Discriminant Analysis", IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 9885-9894. (CCF A)

— Bing Su and Ying Wu. “Learning Distance for Sequences by Learning a Ground Metric”, International Conference on Machine Learning (ICML), 2019, pp. 6015-6025. (CCF A)

— Bing Su and Ying Wu. “Learning Low-Dimensional Temporal Representations”, International Conference on Machine Learning (ICML), 2018, pp. 4761-4770. (CCF A)

— Jiahuan Zhou, Bing Su, and Ying Wu, " Easy Identification from Better Constraints: Multi-Shot Person Re-Identification from Reference Constraints", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2018, pp. 5373-5381. (CCF A)

— Chenqin Cai, Pin Lv, and Bing Su, " Feature Fusion Network for Scene Text Detection", IEEE International Conference on Image Processing (ICIP), 2018.

— Cheng Cheng, Pin Lv, and Bing Su, " Spatiotemporal Pyramid Pooling in 3D Convolutional Neural Networks for Action Recognition", IEEE International Conference on Image Processing (ICIP), 2018.

— Bing Su and Gang Hua. “Order-preserving Wasserstein Distance for Sequence Matching”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 1049-1057. (CCF A)

— Bing Su, Jiahuan Zhou, Xiaoqing Ding, Hao Wang, and Ying Wu, "Hierarchical Dynamic Parsing and Encoding for Action Recognition", Proc. European Conf. on Computer Vision (ECCV), 2016, pp. 202-217. (CCF B)

— Bing Su, Xiaoqing Ding, Changsong Liu, and Ying Wu. “Heteroscedastic Max-Min Distance Analysis”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 4539-4547. (CCF A)

— Bing Su and Xiaoqing Ding. “Linear Sequence Discriminant Analysis: A Model-Based Dimensionality Reduction Method for Vector Sequences”, IEEE International Conference on Computer Vision (ICCV), 2013, pp. 889–896. (CCF A)

— Bing Su, Xiaoqing Ding, Liangrui Peng, and Changsong Liu. “Cross-language Sensitive Words Distribution Map: A Novel Recognition-based Document Understanding Method for Uighur and Tibetan”, International Conference on Document Analysis and Recognition (ICDAR), 2013, pp. 255-259.

— Bing Su, Xiaoqing Ding, Liangrui Peng, and Changsong Liu. “A Novel Baseline-independent Feature Set for Arabic Handwriting Recognition”, International Conference on Document Analysis and Recognition (ICDAR), 2013, pp. 1282-1286.

— Bing Su, Liangrui Peng, and Xiaoqing Ding. SemiBoost-based Arabic character recognition method. Proc. SPIE 7874, Document Recognition and Retrieval XVIII (SPIE DRR), 2011.

社会兼职

期刊评审员：TPAMI，TIP，TCSVT

会议评审员：ICML 2020， NeurIPS 2020，ICME 2020

荣誉获奖

中科院软件所优秀科技人才计划，2019年

中国科学院青年创新促进会会员，2019年