Space-Time Analysis & Research Group

Ling Yin Ph.D. Professor Doctoral Supervisor

– Spatio-temporal Data Mining, Geo AI, Human Spatio-temporal Behavior Modeling, Spatio-temporal Epidemic Modeling, GIS

尹凌博士研究员博士生导师

研究方法：时空数据挖掘、地理空间人工智能、人类时空行为建模、传染病时空建模、地理信息系统
应用领域：公共卫生、交通规划、城市管理
联系方式：中国科学院深圳先进技术研究院F栋11楼邮箱：yinling@siat.ac.cn

Based on urban big data social sensing, geospatial intelligence, and high-performance computing, we aim to develop data intelligence and efficient computing methods capable of analyzing significant spatiotemporal dynamics (such as disease transmission, human mobility, and traffic flow). These methods are applied in public health, urban transportation, emergency management, and big data services. In particular, in recent years, we have focused on the research of spatiotemporal modeling of infectious diseases and intelligent prevention and control methods. Our results have been practically applied to the prevention and control of COVID-19, dengue fever, and influenza, continuously providing technical support to the national and provincial Centers for Disease Control and Prevention.
基于城市大数据社会感知、地理空间智能、高性能计算，构建能够解析重要时空动态（疾病传播、人类移动、交通流动等）的数据智能与高效计算方法，应用于公共卫生、城市交通、应急管理和大数据服务等。特别地，近年聚焦于传染病时空建模与智能化防控方法研究，成果实际应用于新冠、登革热、流感的疫情防控中，持续为全国及各省市疾控中心提供技术支持。

	由尹凌老师等完成的“重大呼吸道传染病疫情防控大数据方法、技术与应用”获由中国测绘学会颁发的2021年度测绘科技特等奖。
	Ling Yin. Fine-grained Geographical Computation of Infectious Diseases Coupled with Population Dynamics. Kang Liu. Study on the Impact of the Initial Outbreak Location of Infectious Diseases on the Risk of Intra-urban Spatiotemporal Transmission.

2021--至今  研究员
2013--2020  副研究员
2011--2013  助理研究员
中国科学院深圳先进技术研究院

2006.08--2011.05
The University of Tennessee at Knoxville
博士

2003.09--2006.07
南京大学硕士
1999.09--2003.07
南京大学学士