Evolutionary reconstruction presents significant challenges, even under the best conditions: inferring evolutionary histories under the simplest tree models involves solving hard optimization problems, which can take months or years to find reasonable solutions. A major part of my research effort involves the development of powerful computational techniques which allow for large-scale estimation of phylogenies (such as are needed for the Tree of Life). We also work on inferring evolution under more complex scenarios, including reticulate evolution (such as horizontal gene transfer and hybridizing speciation) and whole genome evolution (whereby genomes evolve via events that scramble the order of genes within chromosomes). Statistical modelling of evolutionary processes, at all levels, is a fundamental part of the research.
Note: Tandy is one of the PIs on the CIPRES (Cyber-Infrastructure for Phylogenetic Research) project. CIPRES is funded by an $11.6M Information Technology Grant from the NSF, and funds 33 investigators from 13 institutions, to help develop the computational infrastructure for evolutionary biologists so that they can analyze large datasets. The group contains biologists, mathematicians, statisticians, and computer scientists, working together to formulate more meaningful stochastic models of sequence and genome evolution, to develop novel algorithms to analyze large datasets, and to develop novel database technology appropriate for phylogeny reconstruction.