Rafael Frongillo is a postdoctoral researcher at MSR-NYC. He earned his Ph.D. at UC Berkeley, advised by Christos Papadimitriou and supported by the NDSEG fellowship. His research lies broadly in algorithmic economics, drawing techniques from game theory, convex analysis, machine learning, and dynamical systems. Currently, he is focused on conceptual problems in elicitation (i.e. scoring rules, mechanism design, prediction markets).
When not at a whiteboard, Raf can be found making some sort of music, or injuring himself while wearing soccer cleats or attempting acrobatics. For a list of publications and more information, see his homepage.