CMCC Lecture
27 October 2026, 12:00 CET | Online
To join the Lecture, register here
Generative AI offers a new methodological framework for working with complex, heterogeneous climate data and for addressing key challenges in climate modelling and decision-making. Join the CMCC Lecture with Prof. Claire Monteleoni, INRIA Paris and University of Colorado Boulder, to delve deeper into the intersection of generative AI and climate science, discovering how it is reshaping climate research and unlocking new possibilities for modelling, planning and action.
The stunning recent advances in frontier AI models rely on cutting-edge generative deep learning algorithms and architectures trained on massive amounts of text, image, and video data. With different training data, including weather and climate data from observations, reanalyses, and even physical simulations, these same algorithms and architectures can benefit a variety of applications to address climate change, opening new frontiers for climate research.
Many applications aimed at addressing climate change hinge on fundamental challenges of data fusion, interpolation, downscaling, and probabilistic domain alignment. In this CMCC Lecture, Prof. Claire Monteleoni will provide a survey of recent work on developing generative AI methods for these problems, with applications including weather forecasting, climate model emulation and scenario interpolation, and renewable energy planning.
Join the discussion and don’t miss the opportunity to explore how the new frontiers of AI are shaping the future of climate science.
Speaker: Claire Monteleoni, Research Director and Team Leader of ARCHES, INRIA Paris and Professor in the Department of Computer Science, University of Colorado Boulder (on leave)
Discussant: Italo Epicoco, CMCC
Moderator: Soheil Shayegh, CMCC
Claire Monteleoni is a Choose France Chair in AI and a Research Director at INRIA Paris where she leads the AI Research for Climate Change and Environmental Sustainability (ARCHES) team, and a Professor in the Department of Computer Science at the University of Colorado Boulder (on leave). Her research on machine learning for the study of climate change helped launch the interdisciplinary field of Climate Informatics. She co-founded the International Conference on Climate Informatics, which held its 15th annual event in April 2026. As Founding Editor in Chief, she helped Cambridge University Press launch the journal Environmental Data Science.
The event is part of the CMCC Lectures webinar series, which presents frontier topics and solutions in climate sciences and action, through the insights of leading experts. The series provides a platform for prominent scientists to showcase their cutting-edge research and engage in dialogue with peers and stakeholders.