Sumit Mukherjee is currently an Associate Professor in Statistics at Columbia University. He joined Columbia in 2014, shortly after he received his Ph.D. in Statistics from Stanford University. His main research interests lie in the intersection of Mathematical Statistics, Probability, and Combinatorics. One of the common themes of his research is the study of inference in dependent settings, such as exponential families on the space of graphs (ERGMs), rankings (Mallows models) and spin configurations (Ising models). His research has been supported by NSF grants.