个人简历

中国计算机学会(CCF)会员，AAG会员。2000年7月-至今，任教于中国地质大学（武汉）信息工程学院软件工程系；2015年1月-2016年1月，赴美国KSU访问学习一年。近年来主持和参与国家自然科学基金面上项目、国家重点研发计划等项目6项；出版教材1部；指导学生在全国高校互联网应用创新大赛等获奖多项。

主讲课程
近年主要主讲本科生《Java与.Net软件开发》、《Web软件开发》、《计算机网络》、《软件测试》、《面向对象软件工程》、《软件工程专业前沿文献》及研究生《高级程序设计》、《知识图谱》等课程及相关实习实践课程。

研究领域

[1] 时空大数据挖掘与机器学习
[2] 自然语言处理与知识图谱""

近期论文

[1] F. Fang, Y. Yu, S. Li, Z. Zuo, Y. Liu, B. Wan, Z. Luo, Synthesizing location semantics from street view images to improve urban land-use classification, Int. J. Geogr. Inf. Sci. 00 (2020) 1–24. https://doi.org/10.1080/13658816.2020.1831515.
[2] Y. Yu, F. Fang, Y. Liu, S. Li, Z. Luo, Urban Land Use Classification Using Street View Images Based on Deep Transfer Network, in: Urban Intell. Appl., 2020: pp. 83–95. https://doi.org/10.1007/978-3-030-45099-1_7.
[3] Y. Xinyue, G. Junfang, L. Shengwen*, Analyzing Asymmetric City Connectivity by Toponym on Social Media in China, Chinese Geogr. Sci. 30 (2020) 1.
[4] X. Ye, S. Li, Q. Peng, Measuring interaction among cities in China: A geographical awareness approach with social media data, Cities. 109 (2021) 103041. https://doi.org/https://doi.org/10.1016/j.cities.2020.103041.
[5] J. Lee, S. Li, S. Wang, J. Wang, J. Li, Spatio-Temporal Nearest Neighbor Index for Measuring Space-Time Clustering among Geographic Events, Pap. Appl. Geogr. (2020). https://doi.org/10.1080/23754931.2020.1810112.
[6] S. Li, R. Chen, B. Wan, J. Gong, L. Yang, H. Yao, DAWE: A Double Attention-Based Word Embedding Model with Sememe Structure Information, Appl. Sci. 10 (2020) 5804. https://doi.org/10.3390/app10175804.
[7] J. Gong, J. Lee, S. Zhou, S. Li*, Toward Measuring the Level of Spatiotemporal Clustering of Multi-Categorical Geographic Events, ISPRS Int. J. Geo-Information. 9 (2020) 440. https://doi.org/10.3390/ijgi9070440.
[8] X. Kang, B. Li, H. Yao, Q. Liang, S. Li, J. Gong, X. Li, Incorporating Synonym for Lexical Sememe Prediction : An Attention-Based Model, Appl. Sci. (2020). https://doi.org/10.3390/app10175996.
[9] W. Zhen, L. Yang, M. Kwan, Z. Zuo, B. Wan, S. Zhou, S. Li, Y. Ye, H. Qian, X. Pan, Capturing what human eyes perceive : A visual hierarchy generation approach to emulating saliency-based visual attention for grid-like urban street networks, Comput. Environ. Urban Syst. 80 (2020) 101454. https://doi.org/10.1016/j.compenvurbsys.2019.101454.
[10] D. Zhang, X. Zhang, Y. Zheng, X. Ye, S. Li, Q. Dai, Detecting Intra-Urban Housing Market Spillover through a Spatial Markov Chain Model, Int. J. Geo-Information. (2020). https://doi.org/10.3390/ijgi9010056.
[11] J. Gong, S. Li, B. Wan, A Regional Approach to Assessing and Visualizing Spatiotemporal Clustering of Crime Events, Pap. Appl. Geogr. 5 (2019) 1–19. https://doi.org/10.1080/23754931.2019.1611625.
[12] J. Gong, R. Li, H. Yao, X. Kang, S. Li*, Recognizing Human Daily Activity Using Social Media Sensors and Deep Learning, Int. J. Environ. Res. Public Health. 16 (2019) 3955.
[13] J. Gong, S. Li, J. Lee, Space, time, and disease on social media: a case study of dengue fever in China, Geomatica. 72 (2019) 112–126. https://doi.org/10.1139/geomat-2018-0016.
[14] X. Ye, S. Li, X. Yang, J. Lee, L. Wu, The Fear of Ebola: A Tale of Two Cities in China, in: Big Data Support Urban Plan. Manag., Springer, 2018: pp. 113–132. https://doi.org/10.1007/978-3-319-51929-6_7.
[15] J. Lee, J. Gong, S. Li*, Exploring spatiotemporal clusters based on extended kernel estimation methods, Int. J. Geogr. Inf. Sci. 31 (2017) 1154–1177. https://doi.org/10.1080/13658816.2017.1287371.
[16] S. Li, X. Ye, J. Lee, J. Gong, C. Qin, Spatiotemporal Analysis of Housing Prices in China: A Big Data Perspective, Appl. Spat. Anal. Policy. 10 (2017) 421–433. https://doi.org/10.1007/s12061-016-9185-3.
[17] J. Lee, S. Li*, Extending Moran’s Index for Measuring Spatiotemporal Clustering of Geographic Events, Geogr. Anal. 49 (2017) 36–57. https://doi.org/10.1111/gean.12106.
[18] X. Ye, S. Li, X. Yang, C. Qin, Use of social media for the detection and analysis of infectious diseases in China, ISPRS Int. J. Geo-Information. 5 (2016) 156. https://doi.org/10.3390/ijgi5090156.
[19] 李圣文, 凌微, 龚君芳, 周长征, 一种基于熵的文本相似性计算方法, 计算机应用研究. (2016) 665–668.