Mathematical Biology

Research in the field of mathematical biology from the Faculty of Science, University of Melbourne.


David Balding     Application of mathematical, statistical and computational methods in genetics (population, evolutional, medical and forensic genetics) and related areas of biology.

Douglas Brumley     Using microfluidic devices, fluorescent microscopy and high speed imaging in conjunction with mathematical models to investigate fundamental physical principles.

Yaoban Chan     Statistics and mathematical biology.

Edmund Crampin     Modelling heart cells to understand the development of heart disease, interactions between cells and nanoparticles, and computational approaches to study the network of genetic interactions underlying cancer.

Jared Field     Theoretical ecology, evolutionary theory, animal behaviour

Jennifer Flegg     Using mathematical biology to study wound healing, tumour growth and epidemiology.

Roslyn Hickson     Mathematical modelling of infectious diseases, particularly malaria in the Asia-Pacific region.

Barry Hughes     Applied mathematical methods, probability modelling, mathematical biology, continuum modelling, random walks, random environments.

Kim-Anh Le-Cao     Biological data integration, multivariate projection-based methods, computational statistical learning, R software development.

Stephen Leslie     Statistical genomics, including detecting and controlling for population differences in genetic data, typing complex genetic variation, and statistical analyses of the relationship of genetic variants to disease.

Davis McCarthy     Research Fellow

James McCaw     Modelling of host-pathogen-drug dynamics with a focus on influenza and malaria, to develop public health control strategies for emerging and re-emerging infectious diseases.

James Osborne     Numerical and computational methods for mathematical models of biological phenomena.

Guoqi Qian     Statistics theory, biostatistics, bioinformatics, computational statistics and mathematical methods for climatology, ecology and the environment.

John Sader     Plasticity and elasticity, dynamic force spectroscopy, nanocrystal mechanics, atomic force microscopy, continuum modelling, colloidal interactions.

Heejung Shim     Data science, Bayesian statistics, computational biology, statistical genomics, stochastic processes, machine learning, applied statistics.

Michael Stumpf     The inference of mathematical models using statistical inference and machine learning approaches.

Damjan Vukcevic     Biostatistical research with a specialisation in statistical genetics.

Research centres

Mathematical Research Institute MATRIX
MATRIX is an international research institute that runs research programs where world lead researchers in the mathematical sciences, as well as experts from business and industry, can come together.

Melbourne Integrative Genomics (MIG)
We aim to understand biological systems, with a focus on genomes as the blueprint for each system. We are interested in biological systems of different scales.

Research in this area is conducted in the School of Biosciences and School of Mathematics and Statistics.