Visiting Assistant Professor of Physics
Ph.D., Physics -- The College of William and Mary, 1999
Many physical phenomena have been modeled successfully using the idea that what appears at first to be complex behavior is often the result of the identical application of simple rules to a large numbers of autonomous actors in a system. In such systems, there usually exist certain definable quantitative parameters related to the rules of the system. The value of such a parameter can be used to govern the character of the large-scale behavior of the entire system. One range of values will produce global order or simple cyclic behavior, while another range of values results in chaos and unpredictable long-term behavior. However, in a narrow range of values between the other two, very intricate and surprising things occur. In fact, it appears that most of the complexity we see in the natural world is a consequence of what happens when a system is poised between order and chaos
Ontogeny in Living and Artificial Systems
The growth of a single cell into a functional multi-cellular organism (ontogeny) is probably the most fascinating example of self-organization and emergent behavior known. However, many of the structural and dynamic features of biological systems are also seen in economies, ecologies, human societies, and other complex systems. This suggests that the general principles responsible for self-organization and complexity in living organisms might well be universal, and not uniquely dependent on the details of the underlying biochemistry. If we can discover such principles, it may become possible to engineer ontogeny in artificial systems. I'm currently using random boolean network models of the genomic regulatory circuitry of cells to examine their potential for reproducing the main qualitative features seen in real biological development.