长期从事机器学习、最优化与数据挖掘等领域的研究工作，研究内容主要包括多视角学习、不均衡学习、迁移学习、深度学习等。先后为本科生、硕士生、博士生开设《机器学习》、《深度学习专题》等课程。在《IEEE Transactions on Neural Networks and Learning Systems》、《Knowledge-Based Systems》、《Information Sciences》、《Neural Networks》、《Neurocomputing》等国际权威期刊发表SCI收录论文近10篇，在国内外重要学术会议发表论文10余篇，主持国家自然科学基金青年项目1项，中央高校基本科研项目3项。担任Information Sciences、Neurocomputing、knowledge-based systems、Applied Intelligence等期刊审稿人。

邮箱： tjj@swufe.edu.cn

研究方向：机器学习，最优化与数据挖掘

教育背景：

2015.9-2018.7 中国科学院大学 运筹学与控制论 博士2013.9-2015.7 中国科学院大学 运筹学与控制论 硕士2009.9-2013.7 重庆大学 数学与应用数学 学士

研究成果

期刊论文：

[1] Jingjing Tang, *Yingjie Tian, Peng Zhang and Xiaohui Liu. Multiview privileged support vector machines[J]. IEEE Transactions on Neural Networks and Learning Systems, 29(8): 3463-3477, 2018. DOI:10.1109/TNNLS.2017.2728139.

[2] Jingjing Tang, Dewei Li, *Yingjie Tian and *Dalian Liu. Multi-view learning based on Nonparallel Support Vector Machine[J]. Knowledge-Based Systems, 158(2018): 94–108, 2018. DOI: 10.1016/j.knosys.2018.05.036.

[3] Jingjing Tang, *Yingjie Tian, Xiaohui Liu, et. al. Improved multi-view privileged support vector machine[J]. Neural Networks, 106(2018): 96-109, 2018. DOI: 10.1016/j.neunet.2018.06.017.

[4] Jingjing Tang and *Yingjie Tian. A multi-kernel framework with nonparallel support vector machine[J]. Neurocomputing, 266(2017): 226–238, 2017.

[5] Jingjing Tang, *Yingjie Tian and Xiaohui Liu. LGND: A new method for Multi-Class Novelty Detection[J]. Neural Computing and Applications, 2017, DOI: 10.1007/s00521-017-3270-7.

[6] Jingjing Tang and *Yingjie Tian. A Systematic Review on Minwise Hashing Algorithms[J]. Annals of Data Science, 3(4): 445-468, 2016.

[7] 唐静静，田英杰. 基于间隔迁移的多视角支持向量机[J].运筹学学报. 2018, DOI: 10.15960/j.cnki.issn.1007-6093.2018.03.000.

[8] 唐静静，田英杰. 多视角学习综述[J]. 数学建模及其应用. vol. 35, No.3, 2017: 1-16.

会议论文：

[1] Jingjing Tang, *Yingjie Tian and Dalian Liu. “Connected bit minwise hashing for large-scale linear SVM”[C]//2015 IEEE 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015: 995-1002.

[2] Jingjing Tang and *Yingjie Tian. “f-Fractional Bit Minwise Hashing for Large-Scale Learning” [C]//2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). IEEE, 2015, 3: 60-63.

[3] Jingjing Tang and Dewei Li. “Incorporate Hashing with Multi-view Learning”[C]// 2016 IEEE 16th International Conference on Data Mining Workshops(ICDMW). IEEE, 2016: 853-859.

[4] Jingjing Tang, *Yingjie Tian, Guoqiang Wu and Dewei Li. “Stochastic Gradient Descent for Large-scale Linear Nonparallel SVM” [C]//2017 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). IEEE, 2017: 980-983.

[5] Jingjing Tang, *Yingjie Tian and Dalian Liu. “Large-Scale Linear NPSVM via One Permutation Hashing” [C]//2018 IEEE International Joint Conference on Neural Networks(IJCNN). IEEE, 2018.

[6] Dewei Li, Dongkuan Xu, Jingjing Tang and Yingjie Tian. “Metric learning for multi-instance classification with collapsed bags” [C]// IEEE International Joint Conference on Neural Networks(IJCNN). IEEE, 2017: 372-379.

[7] Dewei Li, Jingjing Tang, Yingjie Tian and Xuchan Ju. “Multi-view deep metric learning for image classification” [C]//2017 IEEE International Conference on Image Processing(ICIP). IEEE, 2017: 4142-4146.

所获奖励：

荣获中国科学院大学“优秀学生干部”，“优秀共产党员”，“三好学生”等称号，

荣获中国科学院数学与系统科学研究院“院长优秀奖”，

荣获“重庆市优秀毕业生”称号，

荣获重庆大学“优秀毕业生”，“精神文明先进个人”， “优秀学生“，“优秀共青团干部”等称号,

多次荣获重庆大学学业奖学金。