Synthesis of Statistics, Data Mining and Environmental Sciences in Pursuit of Knowledge Discovery (17w5076)

Arriving in Oaxaca, Mexico Sunday, October 29 and departing Friday November 3, 2017


(University of Maryland Center for Environmental Science)

Yulia Gel (University of Texas at Dallas)

Leticia Ramirez Ramirez (Centro de Investigacion en Matematicas)


In the era of massive multi-platform, multiscale and multi-source data, there appear increasingly more examples that are beyond the scope of any single discipline or field of research practice and that connect across domains with new fascinating capabilities. Such problems must be addressed simultaneously from multiple different perspectives, ranging from statistical sciences, computational and applied mathematics to machine learning to pure and applied studies of Earth systems and their exposure to physical and human influences.

The primary goal of this 5-days workshop is to discuss innovative multi-disciplinary approaches to analysis, modeling and prediction of environmental processes and their societal impact, with a particular focus, on modern statistical and data mining methods for information fusion, uncertainty quantification and propagation. The workshop will highlight a number of such tightly interwoven themes as uncertainty quantification in climate modeling and its impact on end users; climate-induced risk management, adaption and sustainability; climate-sensitive epidemiology, and climate modeling, urban analytics and data mining.