The RIEEE EnviroData Collaborative (EDC) is a new program designed to meet a growing need at Appalachian State University: building environmental data science and modeling capacity through hands-on skill building, shared learning, and collaborative exchange. As the pace of innovation in areas like machine learning, remote sensing, and cloud computing accelerates, researchers across disciplines are seeking opportunities to update and expand their technical skill sets and to continue to learn beyond graduate training.
Through periodic, skill-focused workshops led by both campus experts and invited facilitators, this program will create space for faculty and research staff to gain practical experience with new tools, exchange knowledge, and grow their capacity to conduct cutting-edge, data-intensive research. Beyond individual skills, the EDC will foster a culture of collaboration and interdisciplinary connection. Our goal is to cultivate a vibrant, exchange-driven community that enhances the visibility of environmental data science at Appalachian, increases the impact of faculty research, and strengthens the collective value of RIEEE. Register to attend our upcoming workshop:
Causal Inference in R: An introductionRegister here Instructor: Dennis Guignet, Associate Professor of Economics Date & Time: Friday, February 20, 2026 from 10 a.m. to 12 p.m. Location: Plemmons Student Union, Room 100 Description: We have all heard the maxim "correlation does not imply causation", but causation is often what environmental researchers seek to find. In this workshop we will explore tools to infer causal relationships in real-world data, using an example of environmental pollution and home values. The two-hour workshop will feature a presentation on necessary background material and then segue into an applied R-based example, with plenty of time for discussion and questions throughout. Through this workshop, you will: Gain a basic understanding of some of the key tools for causal inference with observational data, including difference-in-differences, regression discontinuity, and instrumental variables. We will discuss the idea behind these different approaches, their strengths and weaknesses, and to what scenarios they can be applied. Work through an R-based example of the difference-in-difference approach Talk through ways in which these methods might be applied to your own research Meet other environmentally-interested faculty across campus who are seeking to "level up" their research skills and build community
This workshop is designed for faculty or staff with basic R familiarity and provides both conceptual understanding and applied skills relevant across disciplines. Participants should bring their own laptops with a pre-installed copy of RStudio (https://posit.co/download/rstudio-desktop/). |
