ENVR 2022 Workshop: Environmental and Ecological Statistical Research and Applications with Societal Impacts

Brigham Young University, Provo UT

Investigators

Abstract

The "ENVR 2022 Workshop: Environmental and Ecological Statistical Research and Applications with Societal Impacts" will be held in Provo, Utah, on October 6-8, 2022. Environmental Statistics and Data Science (ESDS) is quickly emerging as an integral field for conducting interdisciplinary research in the environmental sciences. Environmental statisticians are charged with processing, summarizing, and analyzing a massive inflow of environmental data from climate models, in situ observations, and remote sensing measurements, to name a few, to understand and mitigate environmental degradation and foster human and ecological well-being. To manage and facilitate growth in ESDS and foster new interdisciplinary research teams, this project will support the above workshop by providing travel support for junior ESDS researchers to attend the workshop. The goals of the workshop are to (i) facilitate interdisciplinary research, (ii) present state-of-the-art methods, and (iii) develop new talent in ESDS. The workshop will include various activities, including panel discussions on the current and future state of ESDS, invited scientific presentations on interdisciplinary topics in ESDS, short courses, a poster session, and team building and brainstorming exercises to establish new research directions and groups. Modern complex questions in the environmental sciences are increasingly turning to more complex datasets from a wide variety of sources for answers. Examples of such complex datasets include, but are not limited to, massive correlated datasets generated from climate models and remote sensing, data collected on non-Euclidean spaces such as river networks, rare-event data on meteorological extremes, and multivariate spatio-temporal data such as pollution compositions. Scientific answers derived from such complex datasets require specialized skills from statisticians and data scientists trained to converse and work with environmental scientists. This project will provide funding to support the participation of junior environmental data science researchers. Speakers from statistics and applied environmental sciences will present their state-of-the-art scientific methods for dealing with data arising in the environmental sciences. Methods discussed will include deep learning for environmental data, computation for massive spatially correlated data, exploiting network information in data collected on river networks, and modern techniques for dealing with point pattern (location) data. These presentations, along with panel discussions, will outline future interdisciplinary research in environmental statistics and data science. More details about the workshop can be found at: https://community.amstat.org/envr/events/workshops/envr2022workshop. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.