汤影，男，教授。电子科大博士，美国Florida大学博士后，美国加州大学圣芭芭拉分校Research Scientist，美国犹他大学访问学者，于2015年开始在成都理工计算机任教。三流数学家，以第一作者发表SCI检索一区和二区论文10余篇。

     研究方向：机器学习/深度学习/AI，动力系统，微分几何，应用数学。

     招生情况：招科研型（主要是写paper）和创业型（主要是产业化）两种类型的学生，希望你有扎实的数学基础或代码能力，尤其欢迎数学系的学生。

     电子邮箱：2729959@qq.com

主要论文：

1. Ying Tang ^#*, Beyond EM: A faster Bayesian linear regression algorithm without matrix inversions, Neurocomputing, 2020, 378: 435-440 (中科院二区).

2. Ying Tang ^#*, Two-Hop walks indicate PageRank order. Pattern Recognition, 2019, 95: 201-210 (中科院一区).

3. Ying Tang ^#*, Fast orthogonal recurrent neural networks employing a novel parametrisation for orthogonal matrices. Signal Processing, 2019, 163: 11-17 (中科院一区).

4. Ying Tang ^#*, Independent component analysis employing exponentials of sparse antisymmetric matrices. Neurocomputing, 2019, 325: 172-181 (中科院二区).

5. Ying Tang ^#*, Li Yinrun, Pairwise comparisons in spectral ranking. Neurocomputing, 2016, 216: 561-569 (中科院二区).

6. Ying Tang ^#, Tang Yuan^*, Iteration on single vector for extracting two extremal eigenpairs of symmetric matrices. Neurocomputing, 2019, 332: 129-136 (中科院二区).

7. Ying Tang ^#*, Li Jianping, Normalized natural gradient in independent component analysis. Signal Processing, 2010, 90(9): 2773-2777 (中科院一区).

8. Ying Tang ^#*, Li Jianping, Notes on “Recurrent neural network model for computing largest and smallest generalized eigenvalue. Neurocomputing, 2010, 73: 1006-1012 (中科院二区).

9. Ying Tang ^#*, Li Jianping, Another neural network based approach for computing eigenvalues and eigenvectors of real skew-symmetric matrices. Computers & Mathematics with Applications, 2010, 60(5): 1385-1392 (中科院二区).

10. Ying Tang ^#*, Li Jianping, Wu Huai, A simple and accurate ICA a1gorithm for separating mixtures of up to four independent components, 自动化学报英文版, 2011, 37(7): 794-799 (中科院二区).

11. Ying Tang ^#*, Li Jianping, 利用参数表示任意维数正交矩阵的ICA新算法, 自动化学报, 2008, 34(1): 31-39.