Cities are the loci of resource consumption, economic activity, and innovation; they are where our looming sustainability problems were born and where those problems must be solved. Given our increasing ability to collect, transmit, store, and analyze data, we have the opportunity to go beyond today’s imperfect and often anecdotal understanding of cities to enable better operations, better planning, and better policy. To understand cities, we must analyze the data exhaust from its components – infrastructure, environment, and people – and how they interact over space and time. While there are already troves of open data about cities, their potential remains largely untapped due to unique challenges related to diversity, scale, and complexity of both urban data and computations required to obtain insights from these data.
I will give an overview of methods and tools we have developed for urban data exploration, including our work on the Sounds of New York City (SONYC) project, then present recent work on using large collections of city imagery to study pedestrian infrastructure with the goal of improving accessibility in cities. I will describe Urban Mosaic, a system for browsing large collections of city images; CitySurfaces, an active learning-based framework that leverages computer vision techniques for classifying sidewalk materials; and the NYU-VPR dataset, aimed at helping the development of assistive navigation for the visually impaired population.
Cláudio T. Silva is an Institute Professor at New York University jointly appointed in the Center for Data Science and the Tandon School of Engineering. He is also affiliated with the Center for Urban Science and Progress (which he helped co-found in 2012) and the Courant Institute of Mathematical Sciences. His research interests include visualization, visual analytics, machine learning, reproducibility and provenance, geometric computing, and computer graphics. He has put his work to practice in urban and sports-related applications. He received his BS in mathematics from the Universidade Federal do Ceará (Brazil) in 1990, and his MS and Ph.D. in computer science at the State University of New York at Stony Brook in 1996. Claudio has advised 20+ Ph.D., 10 MS students, and mentored 20+ post-doctoral associates. He has over 300 publications, including 20 that have received best paper awards. According to Google Scholar, his h-index is 72 and his papers have received over 22,700 citations. Claudio was the elected Chair of the IEEE Technical Committee on Visualization and Computer Graphics (2015–18),
is a Fellow of the IEEE, and received the IEEE Visualization Technical Achievement Award. He was the senior technology consultant (2012-17) for MLB Advanced Media’s Statcast player tracking system, which received a 2018 Technology & Engineering Emmy Award from the National Academy of Television Arts & Sciences (NATAS). His work has been covered by The New York Times, The Economist, ESPN, and other major news media.