My interest is primarily in the evolution of complex (multi-gene) traits in geographically-distributed organisms.  Towards this end, I am currently engaged in the following research topics:

Population structure-  Even with many factors involved in producing a complex trait, if they all act individually and occur randomly and independently they can be studied simply and separately.  This almost never happens in natural populations.  In a typical scenario, related individuals tend to live near each other and mate non-randomly.   Under these circumstances alleles tend to occur in decidedly non-uniform combinations.  Furthermore, alleles (and allele-combinations) do not receive uniform exposure to environmental variables.  It is important then to understand how populations are structured, how population structure comes about, what kinds of genetic patterns it produces, and how they correlate with environments.

Genetic and epigenetic architecture of adaptation and disease-  The same distortion of the genotype-phenotype map that wreaks havoc on association mapping studies distorts the ability of natural selection to act effectively.  Understanding how many loci are involved when an organism needs to adapt to its environment, how many environmental factors are involved in the selective pressure, and how they all interact is necessary to understand how organisms came to be the way they are and what the limits are to how they could become otherwise. The flip side of adaptation is disease.  Understanding the way complex traits came together adaptively can tell us a great deal about what causes them to behave maladaptively. Of great interest is the extent to which these traits are inherited genetically rather than epigenetically.

Association mapping of complex traits and diseases-  When the variation in a trait is controlled by variation at a single locus it is (essentially) trivial to identify how genotype maps to phenotype. As soon as a second locus or additional non-genetic factor begins to influence the trait in question the opportunity arises for disequilibrium to create all sorts of perverse correlations between phenotypes and genotypes regardless of any causal relationship.  Properly mapping the causative factors requires the development of better explicitly multifactorial statistical methods.

Arabidopsis thaliana-  A convenient, globally-distributed, model plant with a ton of available genetic, genomic, and ecological resources.  Additionally, a high rate of self-fertilization leaves it nearly completely homozygous most of the time, rendering it extremely useful for haplotype-based inference.

California oaks-  Charismatic megaflora with real ecological and economic importance. It has a life-history almost the exact opposite of thaliana which leads to radically different forms of population structure.

Humans-  Charismatic megafauna with real medical importance.  A third distinct life-history producing yet another flavor of population structure.

(abstractions)-  Sometimes I find it best to step away from specific organisms and just do theory.