Spatial Data Science 

My research is focused on studying the spatial organization of natural and urban environments using Big data. I am also interested in evaluating the reliability of different Big data sources in the analysis of spatial phenomena.

Currently, I am involved in studying two regional systems. First, I am investigating the geographic distribution of Arctic landscape features such as ice hills using the rich ArcticDEM archives. I am looking if Arctic landscape features distribution and change over time could be explained by an underlying large-scale process such as the thawing of the permafrost.

Second, I am investigating the connection between the spread of vector-borne diseases such as the Zika virus and different human mobility patterns, especially those that are related to tourism. I am analyzing various sources of ‘unstructured’ Big data such as geolocated social media and air travel data to understand how collective human mobility patterns sometimes give rise to a phenomenon such as super spreader communities.

I also have been involved in a couple of efforts to use cyberinfrastructure to increase scientists’ accessibility to spatial Big data repositories and high-performance computing environments. For example, I participated in designing middleware for preparing geospatial data at a scale for deep learning models in a reproducible and transparent way.

The existing of three hubs in a subset of the commuting network of Chicago demonstrates the hierarchical organization of urban land use. My research focuses on studying emergent properties of land use/cover in different contexts such as studying the spread of infectious diseases. (Data credits: census.gov)