Urban Complexity Group at NYU’s Center For Urban Science + Progress is unfolding complexity of urban systems for research, innovation and applications. We apply cutting edge data science, machine learning and network analysis techniques to leverage big urban data for making our cities more smart, efficient, sustainable, resilient – a better place to live in.
Our team brings together faculty, researchers and students – goal-oriented, bright and enthusiastic personalities inspired by smart cities and the promise of data science.
Our projects on urban mobility, transportation, public safety, urban impact assessments as well as fundamental research in network science, big data and complexity are supported by industrial partners and foundations and help innovating the cities we live in.
Our papers are published in top tier journals including Nature’s Scientific Reports, PNAS, Physical Review E, PLOS ONE, Royal Society Open Science, International Journal Of GIS, Applied Geography, Environment And Planing B, EPJ Data Science and many others and push forward the frontier of the modern science.
We promote potential of data science and complexity to broad audience and the students through teaching and public speaking. Our courses include Applied Data Science, Machine Learning, Network Analysis, Scientific Writing.