Auditory systems: Biomechanics and energy flow, active nonlinear response and its coupling to neurological coding.

Modeling biological systems: How do biomechanical systems and biological networks develop to be so robust to environmental and thermodynamic fluctuations?

Nonlinear dynamical systems: Transients, response to noise and steady state limit cycle behaviour.

Probability theory: Bayesian statistics, model comparison, Maximum Entropy deconvolution. Using continuous approximations and Monte Carlo for massively high-dimensional problems. How do we bridge the gap between ‘data processing’ and ‘machine learning’?

Numerical methods: Stochastic differential equations (by direct simulation or Fokker-Planck approaches), Monte Carlo, FDM, and basis-function expansion (FEM) techniques.

Viscoelasticity of equilibrium and non-equilibrium biological systems. Microrheological techniques to measure stress fields in bio-gels; particle-tracking and visualisation.