Márcio has studied the reverse engineering of the mechanisms and the dynamical behavior of complex biochemical pathways.
Andrew works on algebraic statistics; the application of algebraic geometry to machine learning and statistical modeling; causal inference; hidden Markov models; graphical models; singular learning theory; and parameter identifiability.
Kimberly's research focuses on developing a comprehensive nonlinear wave model for the governing physics of the transduction mechanism in the inner ear. This work requires a detailed analysis of the fluid-solid interaction dynamics of the cochlea, as well as the utilization of various perturbation methods and numerical techniques.
Wenrui applies numerical algebraic geometry methods and numerical partial differential equation methods to mathematical problems arising in biology, such as tumor growth, blood coagulation, and deriving efficient numerical methods for large scale computing. The mathematical tools that he uses include PDEs, numerical algebraic geometry, bifurcation analysis, and computational methods.
Karly works in mathematical biology, specifically in population models (ODE and PDE) to study the population dynamics for citrus greening disease and on oncolytic virotherapy.
Leila has studied quality assessment and improvement of limited sampling strategies for accurate estimation of therapeutic related indices that is part of a larger research program on drug related modeling problems.
Jae's research has focused on developing theories and models to understand biological rhythms. Basic questions are: Is there an easier way to find hidden or unknown biochemical interactions? How do complex biochemical networks generate rhythms and control period? He has worked closely with several experimental groups in biology to develop new protocols to test model predictions.
Marc has studied a variety of areas including: spatio-temporal modeling, gene regulatory networks, negative feedback loops, intracellular signaling pathways, systems biology, and cancer modeling.
Joy's research has focused on mathematical models for geographic range shifts of plants and animals under climate change. Math tools include deterministic and stochastic dynamical systems, integral operators, and PDEs.