Kei Tokita works in the area of theoretical and computational studies on statistical mechanics of complex systems like ecological systems, proteins, neural networks, virus evolution and immune response and their learning processes, combinatorial optimization problems etc. Although these subjects appear quite different from each other at first glance, they share a key concept: complexity of interactions. Complex behaviors of these systems emerged from various interactions between diverse elements, e.g. amino acids, neurons, species, viruses and immune cells, etc. Studying them from the point of statistical mechanics, we can make each particular case clearer.
He also interested in new methodologies of scientific computing such as a new Monte Calro method based on extended ensembles implemented on a supercomputer and a PC cluster system with more than 100CPUs.
Rank abundance relations in evolutionary dynamics of random replicators, Y. Yoshino, T. Galla and K. Tokita, Physical Review E, 78, 031924 (2008).
Statistical mechanics and stability of a model eco-system, Y. Yoshino, T. Galla and K. Tokita, Journal of Statistical Mechanics, P09003 (2007).
Statistical mechanics of relative species abundance, K. Tokita, Ecological Informatics, 1, 315-324 (2006).
Species abundance patterns in complex evolutionary dynamics, K. Tokita, Physical Review Letters, 93, 178102 (2004).
Emergence of a complex and stable network in a model ecosystem with extinction and mutation, K. Tokita and A. Yasutomi, Theoretical Population Biology, 63, 131-146 (2003).
M.Sc. in Physics, Waseda University under supervision of Yoji Aizawa
Ph.D. in Physics, University of Tokyo under the supervision of Kunihiko Kaneko
Assistant professor, Department of Science, Osaka University
Visiting researcher, Department of Chemical Biology, Harvard University.
Associate professor, Cybermedia Center, Graduate School of Science and Graduate School of Frontier Biosciences, Osaka University
Visiting researcher, Program for Evolutionary Dynamics, Harvard University