教育背景

• 2002-2006 西安交通大学，学士

• 2006-2012 清华大学，博士

工作经历

• 2012-2015 比利时鲁汶大学（KU Leuven），博士后

• 2015-2016 德国埃尔朗根-纽伦堡大学（FAU），洪堡学者

• 2016-至今  上海交通大学电子信息与电气工程学院，副教授

研究方向

• 机器学习理论

• 机器学习算法及应用

科研项目

• 入选国家特聘专家（青年项目），主持国家自然科学基金面上项目、青年项目以及JWKJW专项、华为、国家电网等项目，参与科技部国家重点研发计划重大专项、上海科委重大项目

代表性论文专著

1. F. Liu*, X. Huang*, Y. Chen, J.A.K. Suykens: Towards a unified quadrature framework for large-scale kernel machines, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press.

2. W. Liu, P. Zhang, Y. Lei, X. Huang*, J. Yang*, M. Ng: A generalized framework for edge-preserving and structure-preserving image smoothing, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press

3. F. Liu*, X. Huang*, Y. Chen, J.A.K. Suykens: Random features for kernel approximation: A survey on algorithms, theory, and beyond, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press

4. S. Chen, Z. He, C. Sun, J. Yang, X. Huang*: Universal adversarial attack on attention and the resulting dataset DamageNet, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press

5. S. Tang, X. Huang*, M. Chen, C. Sun, J. Yang*: Adversarial attack Type I: cheat classifiers by significant changes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(3): 1100-1109, 2021, co-first author

6. F. Liu*, L. Shi, X. Huang, J. Yang*, J.A.K. Suykens: Generalization properties of hyper-RKHS and its applications, Journal of Machine Learning Research, 22: 1-38, 2021.

7. F. Liu, X. Huang*, C. Gong*, J. Yang, L. Li: Learning data-adaptive non-parametric kernels, Journal of Machine Learning Research, 21: 1-39, 2020.

8. L. Shi, X. Huang*, Y. Feng, J.A.K. Suykens: Sparse kernel regression with coefficient-based lq regularization, Journal of Machine Learning Research, 161: 1-44, 2019.

9. X. Huang*, L. Shi, J.A.K. Suykens: Ramp loss linear programming support vector machine, Journal of Machine Learning Research, 15: 2185-2211, 2014.

10. X. Huang*, L. Shi, J.A.K. Suykens: Support vector machine classifier with pinball loss, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(5): 984-997, 2014.