New SFI Omidyar Fellow Joshua Garland’s research has been nothing if not diverse. He took a stringent but powerful mathematical theory and turned it into something more agile and useable by constructing a new paradigm in the way the “workhorse” of nonlinear time-series analysis – delay coordinate embedding – is viewed and operationalized. Along with a Johns Hopkins collaborator, he helped take a new view of how the heart works in which cardiac muscle cells are playing a game of telephone, each cell telling the next cell to fire. Collectively these signals cause the muscles to contract and make the heart pump. Treating these cell interactions as a communication system implies that atrial fibrillation is a communication breakdown.
“From that standpoint, we can use tools from network theory and information theory and come up with treatment protocols that maximize synchronization of the heart,” he says. He also has begun to think about finance and climate. The thread between these seemingly disparate interests? “I’m really interested in how, as you study different systems, you see, in large part, the same thing: the heart does a lot of the same things that traded-financial markets and networks of ice cores do, and I’m interested in what is universally true about the underlying information mechanics of these systems,” he says.
No stranger to the Institute, Garland has taught SFI’s Complex Systems Summer School and the Institute’s Nonlinear Dynamics: Mathematical and Computational Approaches online course. He expects to earn a PhD in computer science from the University of Colorado Boulder this summer. He holds an MS in applied mathematics, also from UC Boulder.