Title: Urban Data Science
The large volumes of urban data, along with vastly increased computing power, open up new opportunities to better understand cities. Encouraging success stories show that data can be leveraged to make operations more efficient, inform policies and planning, and improve the quality of life for residents. However, analyzing urban data often requires a staggering amount of work, from identifying relevant data sets, cleaning and integrating them, to performing exploratory analyses and creating predictive models that take into account spatio-temporal processes. Our long-term goal is to enable domain experts to crack the code of cities by freely exploring the vast amounts of urban data.
In this talk, we will present methods and systems which combine data management, analytics, and visualization to increase the level of interactivity, scalability, and usability for urban data exploration. We will show practical applications of the novel technology in real applications.
Cláudio T. Silva
(on sabbatical at Aviz, INRIA, Paris, France during FY 2018-2019)
Professor of Computer Science and Engineering and Data Science
New York University
Tandon School of Engineering
Brooklyn, NY 11201
Biography: Cláudio T. Silva is Professor of Computer Science and Data Science at New York University. His research has focused on data science, visualization, graphics, and geometry processing. Recently he has been particularly interested in urban and sports applications. He received his BS in mathematics from Universidade Federal do Ceará, and his MS and PhD in computer science at SUNY-Stony Brook.
Claudio is a Fellow of the IEEE and has received the IEEE Visualization Technical Achievement Award. The MLB.com’s Statcast player tracking system, which he helped develop, won the Alpha Award for Best Analytics Innovation/Technology at the 2015 MIT Sloan Sports Analytics Conference, and more recently a 2018 Technology & Engineering Emmy Award from the National Academy of Television Arts & Sciences. Our lab’s work has been covered in The New York Times, The Economist, ESPN, and other major news media.
Claudio’s work has been funded by the National Science Foundation, DARPA, Capital One, NASA, C2SMART— a U.S. DOT Tier-1 University Transportation Center, MLB Advanced Media, NVIDIA, DOE, the Moore-Sloan Data Science Environment at NYU, Labex DigiCosme, and an NYU Provost’s Global Research Institute (GRI) fellowship.