PEER Network seminar on ML/AI in Environmental sciences – Expanding the horizons in environmental monitoring and forecasting

Following the success of the first PEER Network seminar, which introduced the use of Machine Learning (ML) and Artificial Intelligence (AI) in Environmental Sciences, we are excited to announce the second webinar in this series, scheduled for December 5. This session promises to delve into more specialized applications of ML/AI, showcasing innovative research and exploring new methodologies for addressing key environmental challenges.

Building on the first seminar's foundation, this session will highlight projects that span a wide spectrum of environmental research areas, from advanced air quality forecasting to biodiversity monitoring and agricultural productivity assessment. These topics reflect the PEER network's commitment to fostering cross-disciplinary approaches and encouraging collaboration among researchers working at the intersection of AI and environmental science.

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Time (CET, UTC+2)	Topic	Presenter
10 am - 10:05 am	Welcome	TBA
10:05 am - 10:25 am	Forecasting Street-level NO2 and PM2.5 Concentrations in Copenhagen, Denmark using Machine Learning – Some Highlights	Prof. Jibran Khan (Aarhus)
10:25 am - 11:45 am	Nationwide Monitoring of Bird and Bat Populations Using Passive Acoustic Monitoring and Deep Neural Networks	Dr. Kevin Darras (INRAE)
10:45 am – 11:05 am	Environmental Monitoring Across Scales with AI: Promises, Evolution, Trends, and Challenges	Dr. Loïc Dutrieux (EC Europa)
11:05 am - 11:25 am	The potential of irrigation for cereal production in Sub-Saharan Africa: A machine learning application for emulating crop growth at large scale	Dr. Marco Rogna/MSc Ana Klinnert (EC Europa)
11:35 am - Noon	Conclusion - next steps and ideas for collaboration	Kristian Meissner