معرفی
Nicola Gnecco is an Assistant Professor in Statistics at Imperial College London, affiliated with the Statistics section of the Department of Mathematics and the cross-department AI initiative I-X. His research focuses on developing statistical models that integrate machine learning with causality and extreme value theory to enhance robustness and extrapolation capabilities, particularly in distribution generalization and causal inference for extremes.
- PhD in Statistics from the University of Geneva (supervised by Sebastian Engelke)
- Master’s in Statistics from ETH Zurich (supervised by Nicolai Meinshausen)
Prior postdoctoral roles include positions at the Gatsby Computational Neuroscience Unit, UC Berkeley (with Bin Yu), and the Copenhagen Causality Lab (with Jonas Peters and Niklas Pfister), supported by a Swiss National Science Foundation grant (210976). His work aligns with the intersection of causality, machine learning, and statistical modeling for complex systems.
