Lecture by Prof. Claudio T. Silva

For the first time in history, more than half of the world's population lives in urban areas; in a few decades, the world's population will exceed 9 billion, 70 percent of whom will live in cities. Given the growing volume of data that is being captured by cities, the exploration of urban data will be essential to inform both policy and administration, and enable cities to deliver services effectively, efficiently, and sustainably while keeping their citizens safe, healthy, prosperous, and wellinformed. Urban data analysis is a growing research field that will not only push computer science research in new directions, but will also enable many others, including urban planners, social scientists, transportation experts, and so on, to understand how cities work at unprecedented detail.
 
An important longterm goal of our research is to enable interdisciplinary teams to “crack the code of cities”. Over the past 3 years, we have been working on methods and systems that support urban data analysis,with a focus on spatiotemporal aspects. We will describe these efforts, in particular our work on analyzing the NYC taxi dataset, which contains information about over 850 million yellow cab trips that took place in NYC from 2009 to 2013. We will also discuss a number of challenges that have led us to new research paths, pushing us to design new data management, data analysis and visualization techniques.
 
This work was supported in part by the National Science Foundation, a Google Faculty Research award, the MooreSloan Data Science Environment at NYU, IBM Faculty Awards, NYU School of Engineering and Center for Urban Science and Progress.
 
Bio:
Claudio Silva is a professor of computer science and engineering at New York University. His research lies in the intersection of visualization and geometric computing, and he has recently been  particularly interested in the analysis of urban data. He has also developed widelyused visualization and analysis tools, including the open-source VisTrails system.
 
Dr. Silva serves as CUSP’s Head of Disciplines, Professor of Computer Science at NYU Poly, and a faculty member at Courant and the Center for Data Science. Dr. Silva has coauthored more than 200 technical papers and 12 U.S. patents. His current research interests include Big Data and Urban Systems. He has served on more than 100 program committees, and he is currently on the editorial board of the ACM Transactions on Spatial Algorithms and Systems (TSAS), Computer Graphics Forum, Computing in Science and Engineering, Computer and Graphics, The Visual Computer, and Graphical Models. He received IBM Faculty Awards in 2005, 2006, and 2007, and several best paper awards. He is a Fellow of the IEEE. He received the IEEE’s 2014 Visualization Technical Achievement Award for his seminal advances to geometric computing for visualization and contributions to the development of the VisTrails data exploration system.