Mathematical &
Computational Biology
The Mathematical & Computational Biology cluster at Tulane University focuses on the development and application of advanced mathematical models, computational simulations, and sophisticated statistical methods to unravel the complexities of biological systems. This interdisciplinary approach provides fundamental insights into biological phenomena and contributes directly to biomedical science and public health. Our research spans multiple scales, from molecular and cellular processes to organismal locomotion and ecological dynamics.
Faculty in this cluster are particularly adept at bridging the gap between theoretical mathematics and experimental biology. We leverage tools from differential equations, fluid dynamics, and statistical inference to address pressing questions in areas like cancer modeling, phylogenetics, and biostatistics. A significant focus of our group is the study of fluid motion and its interaction with elastic structures, with specific projects investigating the motility of microorganisms like bacteria and spermatozoa, the flow of liquids in flexible tubes such as blood vessels, and the evolution of biofilms. This work is significantly enhanced by strong ties to the Tulane Cancer Center and the Center for Computational Science.
Affiliated Faculty
Our faculty's diverse expertise drives innovation in mathematical and computational biology. Explore their profiles to learn more about their specific research contributions within this cluster.
Ricardo Cortez (Primary)
A leader in computational fluid dynamics, Professor Cortez develops numerical methods for simulating biological fluid flows, from microorganisms to physiological processes, including his widely used Method of Regularized Stokeslets. View Profile »
Lisa J. Fauci (Primary)
A National Academy of Sciences member, Professor Fauci investigates biological fluid dynamics through computational modeling and simulation, providing fundamental insights into organismal locomotion and reproductive mechanics. View Profile »
Lifeng Han (Primary)
Professor Han's research focuses on mathematical modeling of cancer biology and treatment, including dosage optimization and tumor-immune interactions, contributing directly to mathematical oncology. View Profile »
Xiang Ji (Primary)
Specializing in statistical phylogenetics, Professor Ji develops new statistical models and high-performance computing libraries for evolutionary processes, with strong applications in bioinformatics and cancer biology. View Profile »
Michelle Lacey (Primary)
Professor Lacey develops and applies statistical methods to biological data, focusing on statistical genetics, epigenetics, and phylogeny reconstruction, with contributions to the Tulane Cancer Center. View Profile »
Scott McKinley (Primary)
Professor McKinley studies stochastic processes with applications in biological systems, modeling movement from intracellular transport to animal ecology, and developing inference for data tracking particle movement. View Profile »
Kun Zhao (Primary)
Professor Zhao researches nonlinear partial differential equations (PDEs) with applications in mathematical biology and fluid dynamics, including chemotaxis models and bio-fluid flows. View Profile »
Key Initiatives & Resources
- Many faculty collaborate with the Tulane Cancer Center, applying mathematical and statistical methods to oncology.
- Research often involves advanced computational resources and expertise from the Center for Computational Science.
- Explore all faculty profiles in the Mathematics Department Directory.
