Climate change is the defining challenge for the future of human civilization. For many decades, data-driven solutions have been a key component for understanding climate science, and efforts in mitigating and adapting to climate change. However, data science is undergoing a paradigm shift, driven in large by the development of modern machine learning systems that can play complex games, write stories, generate art, and much more. What’s in store for climate change research?
In the ML4Climate initiative led by Prof. Aditya Grover, the members of MINT group work with a range of external collaborators to pioneer the next generation of machine learning algorithms and frameworks that will inform the science, technology, and policy in mitigating and adapting to the changing climate. Our work broadly centers on 4 pillars at the intersection of artificial intelligence and climate change.
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Research: We regularly publish papers at the frontiers of artificial intelligence and climate change. Our current focus areas are in climate science and sustainable energy. See representative works papers here and here.
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Software: We believe in open and reproducible science. Not just doing it, but enabling it. We develop and maintain dataset benchmarks and software for pushing data-driven climate science.
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Education: We develop accessible courses and tutorials to on board students, researchers, and practitioners with different backgrounds.
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Community: Our efforts are aimed at an interdisciplinary audience of researchers, practitioners, policy makers, and concerned citizens. We write perspectives and blog articles for broader audiences, and organize events that engage diverse stakeholders.
news
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Tung and Aditya, along with collaborators from Microsoft, recently released ClimaX, the first foundation model for weather and climate. We are excited by the public response so far, and have many interesting followups in store.
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We launched our PyTorch library ClimateLearn and humbled by the public response so far.
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Aditya is chairing the AI4ClimateScience Bridge Program at AAAI on Feb 8, 2022.
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Hritik, Tung, Shashank, and Aditya presented a tutorial on ML for predicting Climate Extremes at NeurIPS 2022 workshop on Tackling Climate Change with Machine Learning. Selected for spotlight!
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Aditya co-authored 2 papers on climate downscaling using GANs and short-range precipitation forecasting at NeurIPS workshops on AI4Science and Tackling Climate Change with Machine Learning.
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Aditya presented a paper and talk on Rethinking Machine Learning for Climate Science: A Dataset Perspective at the AAAI Fall Symposium on The Role of AI in Responding to Climate Challenges. Selected for long presentation!