Educator

Seminar: John Haldon

 

Seminar presented by John Haldon, Professor of History at Princeton University.

 

SESYNC seminars are open to all interested attendees. Join us in Annapolis!

Seminar: Jessica Gephart

 

Seminar presented by Jessica Gephart, Postdoctoral Fellow at SESYNC.

 

SESYNC seminars are open to all interested attendees. Join us in Annapolis!

Seminar: Eric Tate

 

Seminar presented by Eric Tate, Associate Professor of Geography at University of Iowa.

 

SESYNC seminars are open to all interested attendees. Join us in Annapolis!

Seminar: Sierra Woodruff

 

Seminar presented by Sierra Woodruff, Assistant Professor of Landscape Architecture and Urban Planning at Texas A&M University.

 

Seminar: Ashlynn Stillwell

Energy and Water Sustainability in Cities

Seminar presented by Ashlynn Stillwell, Assistant Professor of Civil and Environmental Engineering at the University of Illinois.

Seminar: Margot Wood

Colombian Coffee, and Transparency and Sustainable Economics (Trase)

Seminar presented by Margot Wood, Associate Scientist at Conservation International.

Colombian coffee is a global industry, and holds important cultural value exemplified through the declaration of the Col

Seminar: Lea Johnson

 

Seminar presented by Lea Johnson, University of Maryland Visiting Fellow.

 

 

SESYNC seminars are open to all interested attendees. Join us in Annapolis!

Seminar: Dean Hardy

The socio-environmental potential for harm: Double dispossession through uneven racial development and climate change

Seminar presented by Dean Hardy, Postdoctoral Fellow at SESYNC.

Accepting Applications: Bayesian Modeling for Socio-Environmental Data 2018

 

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.

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