Educator

2019 Bayesian Modeling for Socio-Environmental Data Short Course

 

Solutions to pressing environmental problems require understanding connections between human and natural systems. Analysis of these systems requires a model that can deal with complexity, is able to exploit data from multiple sources, and is honest about the uncertainty from multiple sources. Synthesis of results from multiple studies is often required. Bayesian hierarchical models provide a powerful approach to analysis of socio-environmental problems.

Beyond the muddy boots: making summer internships count through synthesis workshops

 

It’s a searing summer day on the Eastern Shore of Maryland, and in chest-high waders carrying 30 pounds of soil on your back, the humidity is almost unbearable. We have spent long hours in the field and the lab as a budding undergraduate and graduate researchers, wading through wetlands and tromping through fields for the sake of “research.” The question arises in each of us – “Why am I doing this?”

Seminar: Dr. Matt Huber

Rethinking Climate Change and Inequality: From Carbon Footprints to Class Power.

Seminar presented by Dr. Matt Huber, Maxwell School of Citizenship and Public Affairs at Syracuse University.

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