Priya Donti

ο»Ώ Evan Sherwin ο»ΏΒ ο»Ώ Zane Selvans ο»Ώ Given that Climate TRACE's emissions inventory is now out, I'd be curious to hear what you think of their sector-level methodologiesΒ (particularly in the power sector). Caveat that I haven't had a chance to dig into the methodologies yet.



Tagging in ο»Ώ Felipe Oviedo ο»Ώ, who has done some very relevant work in this area!


That's pretty cool, thanks for sharing!

There's a growing space of companies using ML for climate finance, climate insurance, etc. to try to address the financial forecasting challenge. This article does a good job laying some of them out. We also recently hosted a webinarΒ on "ML for Climate Finance" that is potentially relevant!
There is also some content on the Climate Change AI Wiki pages on electricity supply and demand forecasting. The content on both pages is a bit sparse at the moment, though, so if you do find any interesting papers or initiatives during your search, please do feel free to contribute that knowledge to the Wiki!
I'm not a forecasting expert, but I dug up a few papers and reviews for this forthcoming paper on Machine Learning for Sustainable Energy Systems: https://www.annualreviews.org/doi/abs/10.1146/annurev-environ-020220-061831

I've attached it to this post in case you don't have access at the link above!ο»Ώ
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ο»Ώ Kamlesh Sawadekar ο»Ώ This Twitter post advertising for a PhD position in data science and hydrology for drought modeling seems potentially relevant: https://twitter.com/Tirthankar__Roy/status/1427253752453599237?s=19
Tagging in ο»Ώ Evan Sherwin ο»Ώ, who also works on this topic!
Thanks for sharing, Kartik!

Regarding your "backlog" suggestion, would you mind elaborating further? What kinds of information do you think would be useful to include within a backlog?