His research is focused on integration of kinetics and thermodynamics with constraint-based modeling of genome scale human biological networks. Biochemical networks give rise to high dimensional and nonlinear systems of model equations. Off the shelf algorithms are incapable of reliably finding solutions to such systems. Fortunately, inherent mathematical structure emerges with a parsimonious perspective on biochemical networks and tailored algorithms using powerful variational analysis techniques can be used to reliably solve such systems on genome scale. This research is foundational to efforts to construct predictive models of human biochemistry.