The focus of RiskEcon® Lab @ Courant Institute of Mathematical Sciences is to facilitate the development of software, analytics tools, and semantic libraries that employ high-dimensional datasets to integrate conventional data with web-enabled demographic, biometric, psychometric and sociometric data from innovative sources, by applying a range of computational and analytical methods to commercial, consumer and population-related societal trends, focusing primarily on research and development (R&D).
Our goal is to integrate web-enabled crowdsourcing with machine learning, data-mining, and text-mining, in order to promote research fundamental to large-scale, real world questions, employing applied computational statistics, and robust and scalable data analytic solutions, with three fundamental objectives:
- To foster, promote, and coordinate public-private-academic research partnerships,
- To sponsor, fund, organize and manage big data libraries, and
- To advance NYU’s competency within applied computational statistics.
Recent events demonstrate that large-scale geopolitical and socioeconomic questions may be related to changes in demographics, technology adoption, and consumer and lifestyle choices on the economy. It is crucial for decision-making in both industry and government to understand these patterns and trends, the most critical of which are the emerging effects of changes in technology and consumer behavior on finance, labor, housing, income and wealth distribution, immigration, aging, health and the environment.
RiskEcon® Lab’s primary role is to enable, facilitate and coordinate academic research focusing on these patterns and trends, via the development of commercially-viable, analytic applications employing computational statistical tools in conjunction with innovative and non-traditional data structures. In addition, the lab’s activities involve the advancement of applied mathematical statistics and computational economics, through interdisciplinary post-doctoral, postgraduate, graduate research and education in data science and social computing.