Statistical Inference of high dimensional discrete unknowns from molecular biological, genetic, genomic and geological stratigraphic data sequences is the main focus of our labs research including.  Our work includes the development of theory, methods, and applications of these high-D inferences in the biological science areas of regulatory motif finding, RNA secondary structure prediction, and genome wide studies of epigenetics; and in the geoscience areas of change point estimators of paleoclimate records and probabilistic alignment of geological stratigraphic sequences.  Theoretical interests are focused on high-D ensemble based estimators and Bayesian confidence limits, and application models of stochastic grammars.