Professor Mauricio Barahona
Graphs and dynamics. Community detection. Theory of synchronization. Algorithms for nonlinear signal analysis. Multiscale dynamics and model reduction of bio-systems. Mathematical and computational biology. Machine learning and precision healthcare. Dimensionality reduction and omics data.
Dr Thibault Bertrand
Dr Barbara Bravi
Statistical inference methods for biological systems, in particular to reconstruct dynamics of biological networks and the sequence-function mapping in proteins; an area of particular interest is immunology. Mathematical modelling of stochastic biochemical reactions and model reduction strategies for complex networks. Machine learning, data science and their biomedical applications.
Professor Nick Jones
Networks and Fluctuations - Complex Systems and Systems Biology: Network (graph) analysis, the principles of networks and combinatorics; Transport and development in biological networks; Statistical signal processing; Mitochondrial dynamics; Stochasticity and stem cells; Data science.
Dr Eric Keaveny
Microorganism locomotion and cellular mechanics; Suspensions of interacting and active particles; Mechanics of soft materials and complex fluids; Low Reynolds number hydrodynamics; Numerical methods and computational mathematics.
Dr Anthea Monod
Algebraic approaches to mathematical biology, including topological data analysis and algebraic statistics for biological data structures, such as spatial data, images, phylogenetic trees, networks, and higher dimensional simplices. Specific biological applications of interest are biomedical imaging informatics (MRI and fMRI, histopathology), viral evolution (including reticulate events and recombination), cancer genomics.
Dr Vahid Shahrezaei
Computational Molecular Systems Biology, Design principles that enable cells to function robustly, in spite of significant inherent stochasticity and environmental noise. To this end, a combination of analytical and computational methods is used to investigate the temporal, spatial and stochastic dynamics of biochemical networks.
Dr Philipp Thomas
Stochastic methods to understand single cell dynamics and cell-to-cell variability in biological populations. Agent-based stochastic processes. Stochastic reaction networks, Markov chains and master equations. Inference methods for single-cell data.
|Dr Samuel Johnson||Marie Curie Fellow|
|Dr Iain G Johnston||MRC Fellow|
|Dr Mariano Beguerisse-Diaz||James S. McDonnell Foundation Fellow|
|Dr Thomas Ouldridge||Imperial College Junior Research Fellow|
|Dr Diego Oyarzún||Imperial College Junior Research Fellow|
|Dr Philipp Thomas||Fellow of the Royal Commission for the Exhibition of 1851|