1998.09-2002.06 学士 西安工程大学 计算机科学与技术专业 2002.09-2005.06 硕士 西安交通大学 计算机软件与理论专业 2005.09-2009.06 博士 香港中文大学 计算机科学与工程专业

2009.07-2010.07 副研究员 德国萨尔大学与马克思普朗克信息所 2010.08-2014.05 副研究员 美国普渡大学 2014.05至今 教授 电子科技大学 个人简介 电子科技大学教授、博士生导师，国家特聘青年专家

1. 电子科大985配套经费，先进机器学习平台关键技术研究，主持，2014-2018 2. 国家特聘专家启动经费，先进机器学习平台关键技术研究，主持，2016-2018 3. 国家自然科学基金面上项目，大规模贝叶斯张量分析技术研究，主持，2016-2019 4. 中国科学院网络数据科学与技术重点实验室开放基金，可扩展的贝叶斯学习算法及在大规模社会网络中的应用，主持，2015-2016 5. 中央高校基础科研经费，基于矩阵分布的贝叶斯学习算法及在社会网络分析中的应用研究，2015-2016 6. 国家自然科学基金科学部应急管理项目，基于矩阵分布的统计机器学习算法的专业运动员复杂社会网络构建及应用研究，2015/1-2015/12，主研。 7. 大规模张量分析中的非参贝叶斯学习技术研究 2016.01-2019.12 国家级 国家自然科学基金项目。

[1] Zenglin Xu, Zhe Shandian Qi Yuan and Yu Peng. Association discovery and diagnosis of Alzheimer's disease with Bayesian multiview learning, Journal of Artificial Intelligence Research, v56, p247-268, June 1, 2016. [2] Liu Bin, Zenglin Xu*, Wu Shuang and Wang Fei. Manifold regularized matrix completion for multilabel classification, Pattern Recognition Letters, v80, p58-63, September 1, 2016. [3] Zenglin Xu, Yan Feng and Qi Yuan. Bayesian nonparametric models for multiway data analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence8 (TPAMI), v37, n2, p475-487, February 1, 2015. [4] Zenglin Xu, Rong Jin, Bin Shen and Shenghuo Zhu. Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation, In AAAI'15: Proceedings of the 25th AAAI Conference on Artificial Intelligence. v4, p3115-3121, 2015. [5] Yang Haiqin, Zenglin Xu, Lyu Michael R and King Irwin. Neural Networks, v71, p214-224, November 01, 2015. [6] Chen Shouyuan, Lyu Michael R., King Irwin and Xu, Zenglin. Exact and stable recovery of pairwise interaction tensors, Advances in Neural Information Processing Systems 26, NIPS 2013. [7] Zenglin Xu, Feng Yan, and Yuan (Alan) Qi. Infinite Tucker decomposition: Nonparametric Bayesian models for multiway data analysis, In ICML '12: Proceedings of the 29th International Conference on Machine Learning, v2, p1023-1030, 2012. [8] Zenglin Xu, Feng Yan and Yuan (Alan) Qi. Sparse matrix-variate t process blockmodels. In AAAI '11: Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, v1, p543-548, 2011. [9] Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu and Irwin King. Smooth optimization for effective multiple kernel learning, In AAAI '10: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, v1, p637-642, 2010. [10] Zenglin Xu, King Irwin, Lyu Michael Rung-Tsong and Jin Rong. Discriminative semi-supervised feature selection via manifold regularization, IEEE Transactions on Neural Networks, v21, n7, p1033-1047, July 2010. [11] Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King and Michael R. Lyu. Simple and efficient multiple kernel learning by group lasso, In ICML '10: Proceedings of the 27th International Conference on Machine Learning, p 1175-1182, 2010. [12] Zenglin Xu, Rong Jin, Michael R. Lyu, and Irwin King. Discriminative semi-supervised feature selection via manifold regularization. In IJCAI '09: Proceedings of the 21th International Joint Conference on Artificial Intelligence, p1303-1308, 2009. [13] Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu and Zhirong Yang. Adaptive regularization for transductive support vector machine, Advances in Neural Information Processing Systems 22 (NIPS), p 2125-2133, 2009. [14] Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, and Irwin King. Non-monotonic feature selection. In ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, v382, 2009. [15] Zenglin Xu, Rong Jin, Irwin King and Michael Lyu. An extended level method for efficient multiple kernel learning, Advances in Neural Information Processing Systems 21(NIPS), p1825-1832, 2009. [16] Zenglin Xu, Jin Rong, Zhu Jianke, King Irwin and Lyu Michael R. Efficient convex relaxation for transductive Support Vector Machine, Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference, 2009. [17] Zenglin Xu, Huang Kaizhu, Zhu Jianke, King Irwin and Lyu Michael R. A novel kernel-based maximum a posteriori classification method, Neural Networks, v22, n7, p977-987, September 2009. [18] Zenglin Xu, Rong Jin, Kaizhu Huang, Irwin King and Michael R. Lyu. Semi-supervised text categorization by active search. In CIKM '08: Proceedings of the thirteenth ACM international conference on Information and knowledge management, p1517-1518, 2008. [19] Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, and Michael R. Lyu. Efficient convex relaxation for transductive support vector machine, Advances in Neural Information Processing Systems 20(NIPS), 2007. [20] Zenglin Xu, Irwin King, and Michael R. Lyu. Web page classification with heterogeneous data fusion. In WWW '07: Proceedings of the 16th International Conference on World Wide Web, p1171-1172, 2007. [21] Zenglin Xu, King Irwin and Lyu Michael R. Feature selection based on minimum error minimax probability machine, International Journal of Pattern Recognition and Artificial Intelligence, v21, n8, p 1279-1292, December 2007. [22] Zenglin Xu, Zhu Jianke, Lyu Michael R. and King Irwin. Maximum margin based semi-supervised spectral kernel learning, IEEE International Conference on Neural Networks-Conference Proceedings, p418-423, 2007.