The pervasiveness of cell phones, mobile applications and social media generates vast amounts of digital traces that can reveal a wide range of human behavior. From mobility patterns to social networks, these signals expose insights about human behaviors and social interactions. In this talk, I will discuss approaches that can help local governments and non-profit organizations understand better the spatial dynamics of cities and communities, offering additional insights beyond more traditional sources of information. The ultimate objective is to illuminate the determinants of human dynamics and to understand the role that the context - represented as physical infrastructure and social fabric - plays in people’s mobility experiences, which can ultimately assist in the design of more efficient and inclusive cities.
Vanessa Frias-Martinez is an associate professor in the iSchool and UMIACS, and an affiliate associate professor in the Department of Computer Science. She also leads the Urban Computing Lab at UMD. Frias-Martinez's research areas are data-driven behavioral modeling and spatio-temporal data mining. Her research focuses on the use of large-scale ubiquitous data to model the interplay between human mobility patterns, social networks and the physical environment. Specifically, Frias-Martinez develops methodologies to model and predict human behaviors in different contexts as well as tools to aid decision makers in areas such as poverty, natural disasters or urban planning. Before coming to UMD, she spent five years at Telefonica Research developing algorithms to analyze mobile digital traces. Frias-Martinez is the recipient of a National Science Foundation (NSF) CAREER Award. She received her PhD in computer science from Columbia University.