个人简历

教学工作
本科生课程：《计算机组成原理》
研究生课程：《机器学习》《深度学习与强化学习》
教育背景
博士（硕博连读），2012.9-2019.01，北京交通大学，软件工程，导师：卢苇
联合培养，2016.12-2017.12，美国中佛罗里达大学，图像处理与深度学习
学士，2008.9-2012.6，天津工业大学，计算机科学与技术
主要研究方向为：机器学习，深度学习、半监督深度学习、生成对抗神经网络等
工作经历
2019.1~至今 北京交通大学，软件学院，讲师

研究领域

软件工程"专利
[1]. 中国专利，邢薇薇，魏翔，卢苇，刘渭滨，动态时变环境下寻求全局时间最优路径的方法，授权，2014.5.23，ZL201410222902.X
[2]. 中国专利，魏翔，卢苇，邢薇薇，杨宇翔，张顺利，一种基于多源路径最短距离的交互式图像分割方法，申请，2016.11.21

近期论文

论文/期刊
[1]. Lu S, Wei X, Rao B, et al. LADRA: Log-based abnormal task detection and root-cause analysis in big data processing with Spark[J]. Future Generation Computer Systems, 2019, 95: 392-403.
[2]. Wei X, Boqing G, Zixia L, Lu W, Liqiang W. Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect. International Conference on Learning Representations (ICLR 2018), Accepted as a conference paper.
[3]. Siyang Lu, Xiang Wei, Yandong Li, and Liqiang Wang. Anomaly Detection from Big Data System Logs Using Convolutional Neural Network. In 2018 IEEE Cyber Science and Technology Congress (CyberSciTech). Athens, Greece. August 12-15, 2018.
[4]. Wei X, Lu W, Xing W. Learning Motion Rules from Real Data: Neural Network for Crowd Simulation[J]. Neurocomputing, 2018, 310: 125-134.
[5]. Wei X, Lu W, Bao P, et al. MGA for feature weight learning in SVM—a novel optimization method in pedestrian detection[J]. Multimedia Tools and Applications, 2018, 77(7): 9021-9037.
[6]. Lu W, Wei X, Xing W, et al. Trajectory-based motion pattern analysis of crowds[J]. Neurocomputing, 2017, 247: 213-223.
[7]. Wei X, Lu W, Xing W. A rapid multi-source shortest path algorithm for interactive image segmentation[J]. Multimedia Tools and Applications, 2017, 76(20): 21547-21563.
[8]. Xing W, Wei X, Zhang J, Ren C, Lu W. Hybrid motion graph for character motion synthesis[J]. Journal of Visual Languages & Computing, 2014, 25(1): 20-32.
[9]. Xing W, Wei X, Lu W. Weighted time-based global hierarchical path planning in dynamic environment[J]. Transactions of Tianjin University, 2014, 20(3): 223-231.