TITLE: "EFFICIENT GENERATIVE MODELING FOR WEATHER AND CLIMATE PREDICTION"
SPEAKER: SALVA CACHAY (UC San Diego)
Date: October 23, 2025
Time: 12:00 p.m.
Format: Hybrid
Virtual: Zoom link provided upon registration
In-person: Columbia Innovation Hub, 2276 12th Avenue, Second Floor, Room 202, New York, NY 10027
Salva will present remotely, but attendees are welcome to gather and watch together at the Columbia Engineering Innovation Hub.
*Please note that in-person space is limited.*
__________________________________________________________________________________
Abstract: Accurate and reliable weather and climate prediction is vital for societal planning, disaster mitigation, and understanding climate change. The increasing frequency of extreme weather events demands robust probabilistic forecasts that effectively quantify uncertainty. While generative models, particularly diffusion models, offer a promising path, methodological innovations are needed to overcome crucial limitations in their computational and data efficiency for these large-scale problems. In this talk, I will discuss methodological advancements that address these efficiency bottlenecks by explicitly leveraging the temporal structure of the data to design more efficient generative models for forecasting and emulation problems
Bio: Salva Rühling Cachay is a 4th-year PhD student at UC San Diego working on generative modeling and AI for science under the guidance of Prof. Rose Yu and Prof. Duncan Watson-Parris. His research focuses on developing innovative AI solutions for weather and climate modeling, aiming to advance our understanding and prediction of Earth's complex systems. His work has garnered recognition at top AI conferences, including the best paper award at the ML for Earth System Modeling workshop at ICML 2024. His expertise has led to fruitful research collaborations with leading institutions, including internships at the Allen Institute for AI (Ai2), Jump Trading, and NVIDIA.
Learn More: LEAP
