2000.09-2004.07 大連理工大學套用數學系，套用數學專業，學士；
2004.09-2009.01 大連理工大學數學系，計算數學專業，博士(碩博連讀)；
2008.03-2008.08 Bells-lab (北京)，實習生；
2009.02-2011.10 新加坡南洋理工大學，Research Fellow；
2012.04-2013.10 美國亞利桑那州立大學, 博士後；
2013.10 至今 大連理工大學數學科學學院，副教授。
社會兼職
1. 曾作為《Neural Computing and Applications》、《Neural Processing Letters》、《Neurocomputing》、《IEEE Transactions on Neural Networks and Learning Systems》、《Computational Statistics & Data Analysis》、《IEEE Signal Processing Letters》等期刊審稿人；
2.《Mathematical Reviews》評論員；
研究領域（研究課題）
1. 主持國家自然科學基金青年項目：多任務學習的理論分析與套用，2015-01至2017-12；
1. 主持國家自然科學基金面上項目：基於非獨立同分布樣本的統計學習理論研究與套用, 2015-01至2018-12。
碩博研究方向
機器學習、統計學習理論、隨機矩陣、生物數據分析、深度學習、人工神經網路等。
出版著作和論文
第一作者和通訊作者發表的期刊論文：
1. Chao Zhang and Dacheng Tao. Risk Bounds of Learning Processes for Lévy Processes, Journal of Machine Learning Research (JMLR), vol. 14, pp. 351-376, 2013.
2. Chao Zhang, Jie Yang and Wei Wu. Binary Higher-Order Neural Networks for Realizing Boolean Functions. IEEE Transactions on Neural Networks (IEEE-TNN), vol. 22, no. 5, pp. 701-713, 2011.
3. Chao Zhang, Wei Bian, Dacheng Tao and Weisi Lin. Discretized-Vapnik-Chervonenkis Dimension for Analyzing Complexity of Real Function Classes. IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), vol. 23, no. 9, pp. 1461-1472, 2012.
4. Chao Zhang and Dacheng Tao. Generalization Bounds of ERM-Based Learning Processes for Continuous-Time Markov Chains. IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), vol. 23, no. 12, pp. 1872-1883, 2012.
5. Chao Zhang and Dacheng Tao. Structure of Indicator Function Classes with Finite Vapnik-Chervonenkis Dimensions, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 24, no. 7, pp. 1156-1160, 2013.
6. Chao Zhang, Wei Wu, Xianhua Chen and Yan Xiong. Convergence of BP Algorithm for Product Unit Neural Networks with Exponential Weights. Neurocomputing, vol. 72, no. 1-3, pp. 513-520, 2008.
7. Chao Zhang, Wei Wu and Yan Xiong. Convergence Analysis of Batch Gradient Algorithm for Three Classes of Sigma-Pi Neural Networks. Neural Processing Letters, vol. 26, no. 3, pp. 177-189, 2007.
8. 張超, 李正學, 陳先華, 熊焱. 用線上梯度法訓練積單元神經網路的收斂性分析, 高等學校計算數學學報, vol. 32, no. 3, pp. 261-274, 2010.
9. Xu Xue, Zhang Chao, et al. Drug-symptom networking: Linking drug-likeness screening to drug discovery, Pharmacological Research, vol. 103, pp. 105–113, 2016. (聯合第一作者)
10. Mingchen Yao, Chao Zhang, and Wei Wu. Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples. Discrete Dynamics in Nature and Society, vol. 2015, pp. 1-8, 2015.(通訊作者)
