Ph.D., U of Michigan, 1967
SSPA 2109 | 949-494-4088
Professor Boyd is interested in mathematical models of social behavior, ranging from kinship systems to informal social networks. The methodological questions raised by these endeavors have led him to use probabilistic methods (simulated annealing) to fit structures such as discrete semigroups to network data. Other areas of interest include sociobiology, neural networks, chaos theory, and C++ programming. What ties all these areas together is the emergence of complex structures arising from simple interaction rules.