🧵 1/10 We introduce a new theoretical framework for continuous score-based diffusion models, showing that standard DDPMs contain a built-in spectral failure mode when applied to any multi-scale, power-law physical system.https://arxiv.org/abs/2512.09572

🌊 Research led by #BaskinEngineering Assistant Professor of Applied Mathematics @ashesh6810.bsky.social shows that regional ocean dynamics in the Gulf of Mexico can be better emulated with #AI models—offering new possibilities for navigation and extreme weather monitoring. Read on: bit.ly/4n0AHvj

🚨 New from our group! A stable AI framework for high-res regional ocean modeling-- joint work with Fujitsu Research and NC State led by @baskinengineering.bsky.social PhD students Lenny and @moeindarman.bsky.social. Now out in JGR: Machine Learning & Computation 🌊🤖 🔗 doi.org/10.1029/2025JH000851 🧵

🚨 New preprint alert! “Generative Lagrangian Data Assimilation for Ocean Dynamics Under Extreme Sparsity” is live! 📄 arxiv.org/abs/2507.06479 🌊 Reconstructs high-res ocean states from just 0.1% data using #GenAI. No forward model needed. (1/5)

A physical analysis of #OceanNet, our high-resolution regional ocean digital twins' predictions for the Loop Current led by Anna Lowe in collaboration with Michael Gray, Tianning Wu, and Ruoying He out in AMS AI for Earth systems. journals.ametsoc.org/view/journal...

🌪️ Can #AI predict freak weather events? AI models handle daily forecasts well—but often miss rare extremes. A team including #BaskinEngineering Asst. Prof. @ashesh6810.bsky.social is exploring how adding physics-based principles could improve AI’s accuracy in extreme cases. bit.ly/3Foh7ta

Check out our new work in @pnas.org exploring AI weather's capabilities to predict OOD gray swans.

We released a new pre-print (arxiv.org/abs/2504.15487) on understanding the physics of out-of-distribution generalization (and lack there-of) for turbulence modeling of ocean dynamics. Led by @moeindarman.bsky.social with @pedramh.bsky.social and Laure Zanna.

Looking forward to learning about recent advances in #AI4Climate at the @apsphysics.bsky.social #GlobalPhysicsSummit meeting. Come check out the back-to-back focus sessions, "AI Applications in Weather and Climate I & II," on Tuesday from 9:00 AM to 1:30 PM! summit.aps.org/schedule/?c=...

I am hiring for a #postdocposition for scientific ML + climate dynamics. Folks with deep learning, scientific computing skills; preferably some background in climate, please reach out! This is part of an #NSF project in collaboration with Nicole Feldl and Geoff Vallis. recruit.ucsc.edu/JPF01844

We have released a new pre-print on AI-based long-term regional ocean modeling and downscaling. arxiv.org/abs/2501.05058. This is work led by my PhD students Lenny and Moein with collaborators Roy He, Michael Gray, and Tianning Wu at NCSU and Subhashis Hazarika and Anthony Wong at Fujitsu Research

If you are around at #AGU2024 and interested in ML for climate, please check out these talks from my group and collaborators. 1. Biases, instability, hallucinations in ML emulators of weather and climate. agu.confex.com/agu/agu24/me.... You can also see our paper here: arxiv.org/abs/2304.07029 1/5

Arvind, me, and Jonah released a new pre-print on some pen and paper analysis of fundamental failure modes and old school stability analysis for neural PDEs typically used in AI for Science application. arxiv.org/abs/2411.15101. 1/n

I am hiring for a #postdocposition for scientific ML + climate dynamics. Folks with deep learning, scientific computing skills; preferably some background in climate, please reach out! This is part of an #NSF project in collaboration with Nicole Feldl and Geoff Vallis. recruit.ucsc.edu/JPF01844

Sr Director position (weather forecast) at UChicago's new Human-Centered Weather Forecasting Initiative. Unique opportunity to lead an interdisciplinary team to generate AI- & physics-based forecasts, particularly to support communities most vulnerable to climate variability.