My main field of research is branching processes. A branching process is a stochastic model for a system
of proliferating individuals or particles where assumptions are made about individual behavior such as life-
times and reproduction process, and conclusions are then drawn about behavior on the population level. I
have made contributions to branching process theory (local dependencies, immigration, sampling formulas,
and the "x log x condition") and to biological applications (mutation accumulation in mitochondria, cell de-
synchronization, telomere dynamics, prion dynamics, and lag phase estimation).

I have recently joined a team of researchers who investigate the role of genetic mosaicism in the transmission
of rare disease mutations from parents to children. This research is described here and here.

I have also done work on Poisson approximation, in particular to the problem of the asymptotics of multiple
maxima in discrete distributions.

Another research interest is to develop stochastic models for the Bateson-Dobzhansky-Muller model of speciation.
One paper joint with Trinity biologist Kevin Livingstone and a team of undergraduate students has been published
and another is in preparation.

A side interest of mine is philosophical and methodological aspects of probability and statistics, in particular
as they pertain to scientific inference. In this vein, I have examined some of the mathematical and statistical
arguments presented by proponents of "intelligent design."

For more information, see the links below.

Research publications

Books and book reviews

Articles about intelligent design