On Inferring Structural from Functional Information in Urban Systems
The proliferation of low-cost sensors allows us to collect fine-grained dense data in urban environments. The data can be organized to infer simple functional correlation between different parts of an urban system. However, inferring causation from correlation is difficult if not impossible. In this talk we will focus on a middle ground and use matrix factorization approaches to infer structural information from functional data and use it to understand the flow of vehicular traffic in Doha, Qatar.
Sanjay Chawla is a Principal Scientist in the Data Analytics group at the Qatar Computing Research Institute in Doha, Qatar. He is on leave from University of Sydney Australia where he is a Professor in the School of Information Technologies. He serves on the editorial board of IEEE Transactions of Big Data and Data Mining and Knowledge Discovery Journal. He served as PC CO-Chair of SDM 2016 and PAKDD 2012.