AI for Atmospheric Systems
This is a hybrid event. Please find the Teams link in the Abstract section.
We are building a generative model for cloud structures conditioned on environmental conditions, integrating both high-resolution satellite data and reanalysis data. By being able to generate and reconstruct cloud structures under varying environmental conditions, the model will allow us to reduce uncertainties in future climate predictions and facilitate the detection and quantification of cloud feedbacks across the satellite record. This purely data-driven approach to constraining cloud feedbacks will be complementary to existing work that relies on physics-based models.

Teams link: teams.microsoft.com/l/meetup-join/19%3ameeting_YTFkNTUxNTEtYzVhMS00NmRlLWJkYWItNzZjOTEyMTQxYmRm%40thread.v2/0?context=%7b%22Tid%22%3a%22cc95de1b-97f5-4f93-b4ba-fe68b852cf91%22%2c%22Oid%22%3a%222d6d82c4-6b2c-4f77-b979-7c49923c3b36%22%7d

Bio:
“I am an Encode AI Fellow in the Climate Processes group led by Prof Philip Stier. As part of the Encode fellowship, we are building a generative model for cloud structures with the primary goal is to constrain cloud climate feedbacks. Before starting the fellowship, I was conducting research on compression algorithms for climate and weather data funded by the Embed2Scale project.

I completed my PhD as part of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems here in Oxford. In my research I developed novel Bayesian inference algorithms for models defined through probabilistic programs.”
Date: 13 November 2025, 17:30
Venue: Wolfson College, Linton Road OX2 6UD
Venue Details: Levett Room
Speaker: Dr Tim Reichelt (ENCODE)
Organising department: Wolfson College
Organiser: Dr. Yi Yin (Wolfson College, University of Oxford)
Part of: Oxford Cross-Disciplinary Machine Learning (OxfordXML) Research Cluster Seminar Series
Booking required?: Not required
Booking url: https://oxfordxml.github.io
Cost: Free (Coffee, tea and cake will be provided)
Audience: Public
Editor: Yi Yin