Evolutionary biology is an intellectually rich field that has advanced remarkably through a synergistic interplay between deep understanding of biology and mathematical techniques, especially from probability and statistics. Over the past several decades, the role of computer science in studying biology has grown enormously, and computation has now become an indispensable part of the intellectual mix. Many current problems in evolutionary biology push the limits of computation, and new algorithmic insights are needed to make progress.
The objective of this program was to promote the interaction between theoretical computer scientists and researchers from evolutionary biology, physics, probability, and statistics. The participants of the program collaborated to identify and tackle some of the most important theoretical and computational challenges arising from evolutionary biology. The major themes of the program were sound mathematical modeling, rigorous methods for statistical estimation, and computational scalability.
Long-Term Participants (including Organizers):
Visiting Graduate Students and Postdocs:
Program image by Anand Bhaskar. The image shows several generations of two populations evolving according to the Wright-Fisher model of reproduction, while occasionally exchanging offspring with each other. It was generated as a random sample from this model conditioned on some edges being fixed to form the letters.