Stochastic geometry provides a natural way of averaging out the quantitative characteristics of any network information theoretic channel over all potential geometrical patterns or channel gains present in e.g. a stationary Poisson point process. The talk will survey recent scaling laws obtained by this approach on several network information theoretic channels, when the density of the point process tends to infinity. This approach allows one to predict the asymptotic behavior of spectral efficiency in large wireless networks under densification assumptions. François Baccelli is Simons Math+X Chair in Mathematics and ECE at UT Austin. His research directions are at the interface between Applied Mathematics (probability theory, stochastic geometry, dynamical systems) and Communications (network science, information theory, wireless networks). He is co-author of research monographs on point processes and queues (with P. Brémaud); max plus algebras and network dynamics (with G. Cohen, G. Olsder and J.P. Quadrat); stationary queuing networks (with P. Brémaud); stochastic geometry and wireless networks (with B. Blaszczyszyn). Before joining UT Austin, he held positions at INRIA, Ecole Normale Supérieure and Ecole Polytechnique. He received the France Télécom Prize of the French Academy of Sciences in 2002 and the ACM Sigmetrics Achievement Award in 2014. He is a co-recipient of the 2014 Stephen O. Rice Prize and of the Leonard G. Abraham Prize Awards of the IEEE Communications Theory Society. He is a member of the French Academy of Sciences and part time researcher at INRIA.