Beyond The Publication: Student Submission Shortlisted for Best Impact Award at NeurIPS Climate 2026
an AIClub student's submission has been shortlisted for the Best Impact Award at this year's NeurIPS workshop on Tackling Climate Change with Machine Learning. We aren't naming the paper or its authors here. We want to talk about the conference, what a shortlisting means, and what "impact" means in this setting.
The conference
NeurIPS is one of the world's largest and most prestigious AI research conferences. The Tackling Climate Change with Machine Learning workshop is a long-running event within it, organized by Climate Change AI, a global non-profit that works to catalyze impactful work at the intersection of climate change and machine learning. This workshop is well known to be a select venue for state-of-the-art research in climate science and AI. This year's workshop takes place on December 11, 2026, in Sydney, Australia, as part of a NeurIPS conference spread across Atlanta, Paris, and Sydney.
Workshops at NeurIPS are themselves selected. For 2026, NeurIPS accepted 102 workshops from 454 valid proposals. This workshop brings machine learning researchers together with experts in climate-related fields. Its stated aim is to show that, while machine learning is no silver bullet, it can be a valuable tool for mitigation (reducing emissions), adaptation (helping society respond to the effects of climate change), and climate science (understanding the problem better). Its organizers have said that, to their knowledge, the series draws more attendees than any other academic event on AI and climate change.
What being shortlisted means
Submissions have to be accepted, which means it was reviewed by experts the authors have never met. Being shortlisted for an award means the research was singled out among the accepted work.
Past editions of this workshop have accepted well over a hundred papers and given only a handful of prizes. In 2023, for example, 118 papers were accepted and three received awards. To be considered for an impact award at an event where both AI researchers and climate experts read the work means the reviewers saw real potential in the paper. We'll share the result after the workshop.
What "impact" means here
At this workshop, impact isn't the same as a high score on a benchmark. Submissions are expected to explain how the work has, or could have, a positive effect on climate change, and the series has given prizes for the "Best Pathway to Impact." The climate and machine learning community also points out that the metrics AI researchers use often differ from the ones people in climate fields actually care about.
So impact, in this setting, comes down to a few questions:
- Does it address a real climate problem, in mitigation, adaptation, or climate science?
- Is there a believable path from the research to real use?
- Is it measured in terms the people who would use it care about, not only model scores?
- Is it honest about its limits?
For a student, learning to ask "who would this help, and how?" is as important as learning the method.
Why this matters for our students
We've written about why our students' work is interdisciplinary by design: it starts from a problem in a field, and the student learns enough of that field to ask the right question. This is that idea at its sharpest. A paper that climate experts and AI researchers both read has to hold up in both worlds.
It also shows what a paper can be for a student. As we describe in our post on what makes a good research paper, it's an accomplishment, but it's also a way in to credibility and to people working on problems the student cares about. We're proud of the students involved, and we'll keep you updated.
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If your student has a question in a field they care about, we'd be glad to talk.
Book a free consultation here.
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