Arianna is a Ph.D. candidate in Computational Urban Science and Planning with a background in urban planning, design, and data science. She combines these fields to understand how we can leverage emerging technologies to design more environmentally and socially sustainable urban environments. Her work uses computational and quantitative methods combined with new data sources to understand the interplay between planning policies, the built environment, human behavior, and sustainability. 

She is currently a researcher at Senseable City Lab and the Urban Economics Lab at MIT. Arianna was a summer intern at Microsoft Research, an American Economics Association Summer Fellow at the Richmond Fed, and an alumni of the Santa Fe Institute’s Complex Systems Summer School. 

Before her Ph.D., she completed a Master’s in Urban and Regional Planning at MIT and was awarded the Outstanding Master Thesis Prize for the 2016/17 academic year. Arianna also holds a Licentiate degree in Architecture from Veritas University, Costa Rica.