Environmental Data Science (EDS) is a convergent discipline that focuses on using big data and emerging technologies to drive discovery, solutions, and science to better understand the environment and the interactions between humans and the natural world. EDS draws upon natural and social sciences (such as biology, ecology, geography, sociology, anthropology, geology, hydrology, and economics) and data sciences (such as computer science, information science, mathematics, and econometrics). EDS aims to develop innovative approaches to collect, analyze, and interpret complex environmental data sets to inform policy and decision-making.
About
What is Environmental Data Science?
What We Do
We enable a broad community of researchers to turn environmental data into actionable knowledge and accelerate discovery in Environmental Data Science. We advance team science by using research-based best practices to facilitate collaboration within the center and by studying ESIIL teams to improve basic understanding of multidisciplinary team science.
Who We Are
We are a leading incubator and accelerator of Environmental Data Science (EDS), creating and promoting environments where groundbreaking science happens, next-generation data scientists are trained, multidisciplinary teams thrive, and data, tools, training opportunities, and community foster collaboration.
Our Team
Aashish Mukund
Software Developer
Aashish is a graduate from the Department of Computer Science at CU Boulder
Katherine Siegel
ESIIL Convergent Science Lead
CU Boulder Department of Geography, CIRES
Postdocs
ESIIL Affiliates
ESIIL Advisory Board Members
Former Advisory Board Members
Former Team Members
Join Our Team
Postdoctoral Associate: Apple here by November 20
Please join our mailing list to learn about future opportunities.
