🎓 We’re proud to announce that Jordi Cortés Andrés, one of our PhD students, just defended his thesis: "Regularization in Machine Learning: Advances for Earth Sciences". 🥳 Congratulations on reaching this important milestone in your research journey!

🌍 @ellis.eu #SummerSchool2025 in Jena on AI for Earth & Climate Sciences is underway 👩🏼‍🎓140 PhD students, 👨🏻‍💻13 keynote speakers & 🧑🏼‍🏫 23 tutors are diving into keynotes, hands-on sessions & collaborative projects—bridging #ML & geosciences 🌿🤖 www.ellis-jena.eu/summer-schoo...

✨ Despite #AI technological advances, persistent challenges persist in creating usable data for decision-makers in practice. Dr. Adams-Fuller, Dr. Glenn, & Dr. Fernández-Torres discuss challenges in weather preparedness. ncdp.columbia.edu/ncdp-perspec... @climate.columbia.edu @leapstc.bsky.social

🗣️Yesterday we kicked off #LPS25 with"Advanced AI for Extreme Event Analysis: Hands-on with the AIDE Toolbox" (María González & @miguelangelft.bsky.social). 🌍 About this tool: 💾 github.com/IPL-UV/AIDE/ 📜 tr.ee/AIDEToolbox ℹ️ aidextremes.readthedocs.io/en/latest/

🆕📰 New paper out that studies the #Calibration and the #Uncertainty of Deep Learning Models (DLM) for #Drought. ➡️ "Calibration and uncertainty quantification for deep learning-based drought detection" 🔗 Read it here: tr.ee/CalibrationAndUncertaintyQuantification

📣 IN ONE WEEK: Please join us for the next LEAP Wallerstein Panel Series on #AI + Extreme Weather Preparedness! ✨ "DATA + AI FOR DECISION-SUPPORT AND POLICY" ✨ 📆 Fri., 4/25/25 || 🕙 10a EST 📍 Virtual ℹ️ Info + RSVP: www.eventbrite.com/e/1286345206... #community #climateadaptation #climateresilience

Submit your latest work (papers, demos) in #XAI to the 4th Explainable AI for Computer Vision (XAI4CV) Workshop at #CVPR2025! Details: xai4cv.github.io/workshop_cvp... Submission Site: cmt3.research.microsoft.com/XAI4CV2025 @cvprconference.bsky.social @xai-research.bsky.social

Curious about the recent trends, key challenges, and novel research directions in #explainableAI for #remotesensing? Then check our review paper "Opening the Black Box: A Systematic Review on Explainable Artificial Intelligence in Remote Sensing" (lnkd.in/et9dvHpZ) published at the IEEE #GRSM.

🚨 New paper out in @naturecomms.bsky.social We review how #AI is transforming modeling & understanding extreme weather & climate events like floods, heatwaves, and wildfires🌍🔥💨 🔗Read it! isp-uv.short.gy/AIforExtreme...

Comment: Explainability can foster trust in the use of AI in geoscience @jesper.drams.ch @ecmwf.bsky.social @aifraunhoferhhi.bsky.social www.nature.com/articles/s41...

🌍 New paper: Generative networks for spatio-temporal #gap_filling of #Sentinel2 reflectances @esa.int. 🆓 Free access the first 50 days to the #ISPRS paper @elsevierconnect.bsky.social: isp-uv.short.gy/GapFillingSe... Work developed in the context of Xaida Project. #AI #EarthObservation

🌍 Climate extremes, such as compound heatwaves and droughts, are increasing in both frequency and intensity, yet predicting their impacts on terrestrial ecosystems remains a challenge. Machine learning holds promise, but traditional datasets often struggle to represent these rare events effectively.