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An HU Analytics Ph.D. student’s research paper, recently named “Best Overall Paper” at the Tackling Climate Change with Machine Learning workshop at the NeurIPS2020 Conference, has been featured on

In the article, “A.I. needs to get real—and other takeaways from this year’s NeurIPS,” author Jeremy Kahn notes that (HU Analytics Ph.D. student) Lyra Wang and her collaborators have teamed “to create a machine learning system to automatically predict areas of oil and natural gas drilling sites that are likely to leak methane, the heat trapping gas that is 84 times more potent than carbon dioxide and a major contributor to global warming.”

Wang’s paper, titled “A Machine Learning Approach to Methane Emissions Mitigation in the Oil and Gas Industry,” in a section of the article titled, “An Eye of AI Research.” To view the article, visit this link.

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