Statistical inference for networks: Professor Gesine Reinert, University of Oxford

Professor Gesine Reinert, Oxford University

Research interests
Applied Probability, Computational Biology, and Statistics. In particular: Stein’s method, networks, word count statistics

Have you heard about the phenomenon that everyone is six handshakes away from the President? The six degrees of separation hypothesis relates to a model of social interactions that is phrased in terms of a network - individuals are nodes, and two individuals are linked if they know each other. Networks pop up in a variety of contexts, and recently much attention has been given to the randomness in such networks. My main research interest at the moment are network statistics to investigate such networks in a statistically rigorous fashion. Often this will require some approximation, and approximations in statistics are another of my research interests. It turns out that there is an excellent method to derive distances between the distributions of random quantities, namely Stein's method, a method I have required some expertise in over the years. The general area of my research falls under the category Applied Probability and many of the problems and examples I study are from the area of Computational Biology (or bioinformatics, if you prefer that name).

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