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My research is concerned with the evolutionary history of information processing mechanisms in biology and culture, with an emphasis on robust information transmission, signaling dynamics and their role in constructing novel, higher level features. The research spans several levels of organization finding analogous processes in genetics, cell biology, microbiology and in organismal behavior and society. At the cellular level I have been interested in molecular processes, which rely on volatile, error-prone, asynchronous, mechanisms, which can be used as a basis for decision making and patterning. I also investigate how signaling interactions at higher levels, including microbial and organismal, are used to coordinate complex life cycles and social systems, and under what conditions we observe the emergence of proto-grammars. Much of this work is motivated by the search for 'noisy-design' principles in biology and culture emerging through evolution that span hierarchical structures. In addition to general principles there is a need to provide an explicit theory of evolutionary history, a theory accounting for those incompressible regularities revealed once the regular components have been subtracted.
Research projects includes work on the molecular logic of signaling pathways, the evolution of genome organization (redundancy, multiple encoding, quantization and compression), robust communication over networks, the evolution of distributed forms of biological information processing, dynamical memory systems, the logic of transmissible regulatory networks (such as virus life cycles) and the many ways in which organisms construct their environments (niche construction). Thinking about niche constructing niches provides us with a new perspective on the major evolutionary transitions.
Many of these areas are characterized by the need to encode heritable information (genetic, epigenetic, auto-catalytic or linguistic) at distinct levels of biological organization, where selection pressures are often independent or in conflict. Furthermore, components are noisy and degrade and interactions are typically diffusively coupled. At each level I ask how information is acquired, stored, transmitted, replicated, transformed and robustly encoded. With collaborators I am engaged in projects applying insights from biological information processing to electronic, engineered systems.
The big question that many of us are asking is what will evolutionary theory look like once it has become integrated with the sciences of information, and of course, what will these sciences then look like?