Esteban Moro, MIT Media Lab and Universidad Carlos III (Madrid)
Segregation is hurting our societies and specially our cities, where the fact that we live apart from other racial, economical or social groups carries tremendous economical and societal consequences. Not only for the people living in poor neighborhoods, but for the region as a whole. Most studies still describe people’s segregation patterns using census areas. However, encounters between people happen in places, not census areas, so our understanding of segregation still relies on very coarse-grained spatial description of how people interact or encounter in our cities. Using a massive dataset of high spatial resolution movements of 4.5 million people in 11 of the largest metropolitan areas in the US we have studied how encounters of different economic groups happen in our cities to determine the economic segregation at the level of places (venues) and individual users. We’ve found that some type of places (some restaurants, education, religious places) are constantly segregated across US, while some other (art exhibits, science museums, hospitals, etc.) are not. Furthermore, we were able to model individual segregation and found that most of the segregation/isolation that individuals experience in their daily lives does not depend on where they live, but on their individual behavioral patterns (type of places visited, social exploration, etc.) We discuss the implications of our results in the context of future development of areas and in the ever-changing evolution of our cities.
Esteban Moro is a researcher, data scientist and professor at MIT Media Lab and Universidad Carlos III (UC3M) in Spain. He was previously researcher at University of Oxford. A native from Salamanca (Spain) he holds a PhD in Physics and is an affiliate faculty at Joint Institute UC3M-Santander on Big Data at UC3M and the Joint Institute of Mathematical Sciences (Spain). He has published extensively throughout his career (more than 60 articles) and led many projects funded by government agencies and/or private companies. Esteban has served as jury in many Data Science and Big Data challenges, is editor of several journals and has advised many PhD students.
Esteban’s work lies in the intersection of big data and computational social science, with special attention to human dynamics, collective intelligence, social networks and urban mobility in problems like viral marketing, natural disaster management, or economical segregation in cities. Apart from his academic career he has worked closely with companies like Twitter, Telefónica, and BBVA in the use of massive datasets to understand problems like how humans communicate, how political opinion spreads in social networks or building alternative wellbeing indexes. He has received numerous awards for his research, including the “Shared University Award” from IBM in 2007 for his research in modeling viral marketing in social networks and the “Excellence in Research” Awards in 2013 and 2015 from UC3M.
Esteban’s work has appeared in major journals including PNAS and Science Advances and is regularly covered by media outlets such as The Atlantic, The Washington Post, The Wall Street Journal, El País (Spain).