### Research

## Research Interests

#### Epidemic spreading in non-homogeneous systems

Most results in mathematical epidemiology are based on
fairly strong assumptions of random mixing in susceptible populations.
However, real contact networks display a high degree of complexity
such that a more detailed description of the interactions is needed.
Based on the framework graph theory, I'm trying to understand the
effects of such heterogeneity on pathogen evolution in such complex
host systems.

#### Stability of ecological networks

The interaction of species in ecosystems can be
represented by networks, in which species either prey on each other
(food webs or trophic networks) or where interactions between species
are mutually beneficial (mutualistic networks). The criteria which
determine the stability of such networks is different for trophic and
mutualistic networks, however. Interactions between species in real
eco-systems are both trophic and mutualistic and thus non-trivial
situations can arise when mixing the two. Using simulations of species
interactions on networks based on real data, I investigate the change
in stability conditions for networks that are both mutualistic and
trophic.

#### Phylodynamics of infectious diseases

Phylodynamic inference estimates epidemiological
parameters from pathogen sequence data that is collected during an
epidemic outbreak. Until recently, the statistical models that have
been employed made crude assumptions about the underlying dynamical
model. I develop phylodynamic models that account for realistic
epidemiological dynamics, such as SIR-type model.