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Garry Sotnik Member since: Friday, April 06, 2018 Full Member Reviewer

GARRY SOTNIK is a Lecturer with the Sustainability Science and Practice Program in the School of Earth, Energy and Environmental Sciences. He is a systems scientist with research focused on identifying robust strategies in contexts defined by deep uncertainty and global climate change. Garry develops and implements agent-based computer simulation models that explore co-evolutionary interactions among human cognition and behavior, on the one end, and biophysical conditions, on the other. He has experience designing and teaching courses on agent-based modeling and on different approaches to modeling coupled human and natural systems. Garry holds a Ph.D. in Systems Science from Portland State University and an M.A. in Economics and a B.S. in Management from Boston University.

agent-based modeling, cognition

Kenneth Aiello Member since: Thursday, January 23, 2020 Full Member

Ph.D., Biology and Society, Arizona State University, B.S., Sociology, Arizona State University,, B.S., Biology, Arizona State University

Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.

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