In Bailis’s dissertation, Coordination Avoidance in Distributed Databases, he addresses a perennial problem in a network of multiple computers working together to achieve a common goal: Is it possible to build systems that scale efficiently (process ever-increasing amounts of data) while ensuring that application data remains provably correct and consistent? These concerns are especially timely as Internet services such as Google and Facebook have led to a vast increase in the global distribution of data. In addressing this problem, Bailis introduces a new framework, invariant confluence, that mitigates the fundamental tradeoffs between coordination and consistency. His dissertation breaks new conceptual ground in the areas of transaction processing and distributed consistency—two areas thought to be fully understood. Bailis is an Assistant Professor of Computer Science at Stanford University. He received a PhD in Computer Science from the University of California, Berkeley and his AB in Computer Science from Harvard College.