David Wolpert received degrees in physics from the University of California, Santa Barbara, and from Princeton University.  He is currently a Senior Computer Scientist at NASA and a consulting professor at Stanford.  He was formerly head of a data mining group at IBM Almaden Research and a Postdoc at the Santa Fe Institute. His work primarily concerns how to design collectives of complex adaptive agents to achieve a global goal (i.e., distributed control and/or optimization). Other work investigates the bounds on computation that hold in broad classes of physical universes, and the use of self-dissimilarity as a complexity measure. He also works on extending game theory to sub-rational games using techniques from statistical physics.