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ETH Zürich
Phone: +41 44 632 93 17 |
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.
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.
Gabriel Leventhal is a PhD student in Sebastian Bonhoeffer's group at the ETH Zurich.
Gabriel Leventhal studied physics at the Swiss Federal Institute of Technology Lausanne (EFPL) and received his Master's in Statistical Physics from the EPFL in 2008. From 2005 to 2006 he was at The Hong Kong University of Science and Technology as part of an undergraduate exchange program, where he worked with Kwok Yip Szeto on complex networks, sequence analysis and epidemic spreading. He wrote his Master's Thesis, Spectral Coarse Graining in Ising Spin Systems at Indiana University under the joint supervision of Alessandro Flammini (School of Informatics, Indiana University) and Paolo De Los Rios (Laboratory of Statistical Biophysics, EPFL). Before beginning his PhD with Sebastian Bonhoeffer in 2009 he volunteered for the Clinton Foundation HIV/AIDS initiative in West Africa.
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