Weather and climate impact people in a multitude of ways, influencing what we wear, what food and resources we buy, and how we respond in times of emergency. A vast amount of data exists about weather — from heat waves to storms and floods — and this data offers powerful opportunities for applied learning and entrepreneurial problem-solving. The Cloud Analytics Faculty Fellows (CAFF) program supports faculty in designing innovative, data-rich classroom experiences using NOAA weather and climate datasets and modern cloud computing tools. These resources enable engaging, real-world learning that enhances student data literacy, entrepreneurial thinking, and climate awareness by connecting NOAA data to regional business or community use cases.
Funded by the Appalachian Regional Commission (ARC) and delivered in partnership with the High Technology Foundation of West Virginia (HTF), NOAA’s Open Data Dissemination (NODD) initiative, and a cohort of implementing institutions (Appalachian State University, West Virginia University (WVU) and Berea College), the program cultivates a regional ecosystem of interdisciplinary faculty and students engaged in applied climate education, cloud analytics, and innovation.
2026 Cloud Analytics Faculty Fellows
Please join RIEEE is congratulating the inaugural cohort of Appalachian State’s Cloud Analytics Faculty Fellows (CAFF) program! The 2026 fellows are:
- Shishir Shakya (Economics/WCOB), Proposal Title: NOAA Cloud Analytics for Business Statistics and Econometrics Education
- Benjamin Sanchez Andrade (Sustainable Technology and the Built Environment/CFAA), Proposal Title: Integrating NOAA Cloud Analytics into BIM Education: A Climate-Driven Bridge Scour Digital Twin Assignment for Regional Resilience
- Pia Albinsson (Marketing and Supply Chain Management/WCOB), Proposal Title: Weather-Driven Market Opportunities: Using NOAA Data to Inform Entrepreneurial Marketing Decisions
- Scott Marshall (Geological and Environmental Sciences/CAS), Proposal Title: Integrating NOAA Cloud-Hosted Data and Entrepreneurial Thinking into GES 3455
- Mohammad Ali Javidian (Computer Science/CAS), Proposal Title: Robust River Monitoring at Scale: Low-Cost AI Systems with Failure-Aware Fusion and Safe Alerts
