受教育经历：
· 2008.9-2012.6，武汉大学，电子科学与技术，学士
· 2012.9-2017.6，武汉大学，微电子学与固体电子学，直博
科研与学术工作经历：
· 2017.07-2019.07，武汉科技大学，信息科学与工程学院，博士后
· 2017-07-2020-12，武汉科技大学，信息科学与工程学院，讲师
· 2020-12-2024-11，武汉科技大学，信息科学与工程学院，副教授
· 2024-11-至今， 武汉科技大学，电子信息学院，教授
人才计划项目：
· 湖北省“楚天学者计划”楚天学子
主持及参与项目：
1. 国家自然科学基金委员会, 面上项目, 62176192,图信号处理及其在化合物QSAR/QSPR模型学习与植物性状网络分析中的应用, 202201-202512, 在研, 主持
2. 国家自然科学基金委员会, 青年项目, 61801338, 图信号的小波滤波器组设计及其在碳氢化合物QSPR研究上的应用, 2019-01至2021-12, 主持, 已结题
3. 国家自然科学基金委员会, 青年项目, 61801339, 基于特征学习的外辐射源雷达低可观测目标检测方法研究, 2019-01至2021-12, 已结题, 参与
已发表文章：
[10] Chunyu Hao, Xiaoying Song*, Fang Yang, Wanning Zheng, Yufeng Zhou, Fusion of individual and population graphs in a GNN brain disease network, in the 27th International Conference on Information Fusion, Venice, Italy, 2024.7.7-2024.7.11.
[9] Xiaoying Song, Gaoya Wen, Li Chai*, Graph signal processing based nonlinear QSAR/QSPR model learning for compounds, Biomedical Signal Processing and Control, 2024, 91: 106011.
[8] 汪鑫欣，宋笑影*，柴利，基于子图相似性的多动症患者脑网络分析，数据采集与处理，2023,38(5):1142-1150.
[7] Xiaoying Song, Li Chai*, Graph signal smoothness based feature learning of brain functional networks in schizophrenia, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, 31: 3854-3863.
[6] Xiaoying Song, Ke Wu, Li Chai*, Brain network analysis of schizophrenia patients based on hypergraph signal processing, IEEE Transactions on Image Processing, 2023, 32: 4964-4976.
[5] Xiaoying Song, Li Chai*, Jingxin Zhang, Graph signal processing approach to QSAR/QSPR model learning of compounds, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(4): 1963-1973. （入选湖北省2021-2023年百篇优秀科技论文）
[4] Xiaoying Song, Bing Liu, Qijun Huang*, Ruihan Hu, Design of high-resolution quantization scheme with exp-Golomb code applied to compression of special images, Journal of Visual Communication and Image Representation, 2019, 56: 102648.
[3] Xiaoying Song, Qijun Huang*, Sheng Chang, Jin He, Hao Wang, Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction, Medical & Biological Engineering & Computing, 2018, 56(6): 957–966.
[2] Xiaoying Song, Qijun Huang*, Sheng Chang, Jin He, Hao Wang, Three-dimensional separate descendant-based SPIHT algorithm for fast compression of high-resolution medical image sequences, IET Image Processing, 2017, 11(1): 80-87.
[1] Xiaoying Song, Qijun Huang*, Sheng Chang, Jin He, Hao Wang, Novel near-lossless compression algorithm for medical sequence images with adaptive block-based spatial prediction, Journal of Digital Imaging, 2016, 29(6): 706-715.
教学情况：
1.《信号与系统》，56学时，本科生课程
2.《机器学习及数据挖掘》，32学时，研究生课程
