Nicola Gnecco

I am a Lecturer (Assistant Professor) at Imperial College London, in the Statistics section within the Department of Mathematics. I am also a faculty member at I-X, an Imperial’s cross-department initiative in AI.

My vision is to develop statistical models that are flexible enough to account for recent advances in machine learning while benefiting from causality and extreme value theory for better robustness and extrapolation. My research spans two directions: distribution generalization from a causal perspective and causal inference for extremes.

Previously, I was a visiting postdoctoral researcher @ Gatsby Computational Neuroscience Unit working with Arthur Gretton, a postdoctoral researcher @ Yu Group, UC Berkeley working with Bin Yu, and a postdoctoral researcher @ Copenhagen Causality Lab, University of Copenhagen, working with Jonas Peters and Niklas Pfister. During my postdoc I was supported by a research grant (210976) from the Swiss National Science Foundation. I obtained a PhD in Statistics supervised by Sebastian Engelke from the University of Geneva, and a master’s thesis in Statistics supervised by Nicolai Meinshausen from ETH Zurich.

Keywords: causal inference, distribution generalization, extreme value theory.