Catastrophic events in the complex world: mathematics and statistics of extremes in the age of machine learning (26w5651)

Organizers

Rafal Kulik (University of Ottawa)

Gloria Buritica (AgroParisTech)

Natalia Nolde (The University of British Columbia)

Gennady Samorodnitsky (Cornell University)

Stilian Stoev (University of Michigan)

Description

The Banff International Research Station will host the "Catastrophic events in the complex world: mathematics and statistics of extremes in the age of machine learning" workshop in Banff from August 9 - 14, 2026.


Catastrophic events, even though they happen rarely, have a significant impact when they occur.
Disastrous climate, financial, insurance or complex network failure events can have devastating social and
environmental consequences. A complete risk analysis for modelling and prediction purposes requires
understanding how these extreme, rare events occur, and what are the main drivers causing
them. Machine learning methods open the road for methodological developments to forecast these
extreme events and discover their complex, possibly high-dimensional nature.



The aim of this workshop is to bring together researchers contributing to closely related, but culturally disconnected research communities: extreme value theory and machine learning. The goal is to discuss new
directions and open mathematical problems, and foster further collaboration. The leading experts
will introduce young researchers, postdocs and graduate students to the state-of-the-art in the field.