Interview with Erica Kimei: Using ML for studying greenhouse gas emissions from livestock

Greenhouse gas emissions are a key driver of climate change. We asked Erica about her work, and her experience at the AfriClimate AI workshop at the Deep Learning Indaba, where her research won an award. I am Erica Kimei, a PhD candidate at the Nelson Mandela African Institution of Science and Technology in Tanzania (NM-AIST), and an assistant lecturer at the National Institute of Transport. My research focuses on leveraging machine learning and remote sensing technology to monitor and forecast greenhouse gas emissions from ruminant livestock. This work aims to contribute to sustainable agricultural practices by enabling better management of emissions and addressing the climate impacts of livestock farming.