报告主题：Modeling and understanding urban activity patterns based on crowdsourced data
报告人：德国海德堡大学 黄炜 博士
How people live, work and play within urban arears plays an essential role in designing and building a city and understanding social phenomenon. Recently, cities have become more diverse and complex than ever before, leading to a variety of urban problems. To deal with such unprecedented challenges, one key solution is to understand the mechanism of the interaction between citizens and urban environments. This talk reports some work on using machine learning and spatial data analysis to explore urban activity and mobility patterns and their influences on urban systems based on urban sensor data and geo-social media data.
Wei Huang is a Postdoctoral Fellow in the GIScience Research Group at the Institute of Geography, Heidelberg University, Germany. He received his PhD degree from the Department of Civil Engineering (Geomatics stream) at Ryerson University, Toronto, Canada in 2016. His research interests lie at the intersection of GIScience, urban environments, and computational social science, focusing on using GIS, geospatial big data and new technologies to progress the understanding of the mechanism of the interaction between human activities and mobility, social events and urban systems. He has published 12 papers in peer-reviewed journals, delivered six oral presentations in internal conferences and won several awards including the U. V. Helava Award Best Paper 2016 (ISPRS Journal of Photogrammetry and Remote Sensing) and the 1st Place Doctoral Best Paper Award in the International Conference on Location-based Social Media Data, Athens, Georgia, USA, in 2015.