David is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and at Mila Quebec AI Institute. He is a Co-founder and Chair of Climate Change AI, a global initiative to catalyze impactful work at the intersection of machine learning and climate change. David received his Ph.D. in Applied Mathematics from MIT. He is a former NSF Mathematical Sciences Postdoctoral Research Fellow, NSF Graduate Research Fellow, and Fulbright Scholar, and was named to the MIT Technology Review’s 2021 list of “35 Innovators Under 35.”
What David likes to study
David’s research focuses on applications of machine learning to climate change mitigation and adaptation, encompassing such diverse areas as biodiversity monitoring, electrical grid optimization, agricultural remote sensing, carbon stock estimation, accelerated materials discovery, and climate model emulation.
What David recommends
The following are some interesting items you might want to check out:
Tutorial on machine learning and climate change at the International Conference on Machine Learning (ICML): https://icml.cc/virtual/2022/tutorial/18443
Overview paper on machine learning and climate change: https://dl.acm.org/doi/10.1145/3485128
Policy report for the Global Partnership on AI (GPAI) with recommendations for governments: https://www.gpai.ai/projects/climate-change-and-ai.pdf
Climate Change AI newsletter, with monthly listings of jobs, events, datasets, papers, funding, etc: https://www.climatechange.ai/newsletter