معرفی
Sean S. Downey is an Associate Professor in the Department of Anthropology at The Ohio State University, affiliated with the College of Arts and Sciences. He is also associated with the Sustainability Institute and the Translational Data Analytics Institute at OSU, where he contributes to interdisciplinary research on complex socioecological systems. He is currently leading the development of a new Bachelor of Science in Computational Social Science.
His research focuses on applying complex adaptive systems theory to understand how Indigenous customary practices—particularly in swidden agriculture—contribute to long-term socioecological sustainability. His work integrates field experiments, agent-based modeling, and remote sensing to study human-environment interactions in regions such as the Toledo District of Belize and historical Neolithic Europe.
Dr. Downey's recent publications highlight a strong trend in using computational and experimental methods to analyze sustainability in traditional agricultural systems. His studies combine anthropology with data science, focusing on topics like public goods games in Maya communities, drone-based ecosystem monitoring, and early warning signals of societal collapse. This interdisciplinary approach bridges environmental science, social theory, and complexity science.
Scientific Awards:
- National Science Foundation CAREER Award
Sean Downey has secured competitive external funding, including the prestigious NSF CAREER award, supporting his work on Q’eqchi’ Maya social norms and tropical forest dynamics. He actively collaborates with leading scholars such as J. Stephen Lansing and Stefan Thurner, contributing to high-impact research on cultural evolution, language transmission, and sustainable land use. While formal advisees are not listed, his leadership in curriculum development and research suggests a strong mentoring role.
He is involved in advanced modeling initiatives and is building academic infrastructure through the new Computational Social Science program, reflecting a commitment to translational, data-driven anthropology.
