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This monograph provides a summary of the basic theory of branching processes for single-type and multi-type processes. The first chapter develops the branching process theory, while in the second chapter two applications to population and epidemic processes of single-type branching process theory are explored.

This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons.

This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As applications, the author evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis.

Their research is focused on probability and stochastic processes with applications in biology and other areas of science and technology.These notes are based in part on lectures given by Professor Anderson at the University of Wisconsin - Madison and by Professor Kurtz at Goethe University Frankfurt.