The AI for Earth program applies machine learning and data science to hard challenges in agriculture, water, climate, and biodiversity. In this talk, we will discuss how the AI for Earth team, Microsoft Research, and AI for Earth grant recipients are using machine learning to enable precision agriculture, to predict outbreaks of disease, to detect poachers in real time, and to classify animals for conservation. Finally, we will briefly provide details on the AI for Earth grant program to obtain resources for everyone to work on these challenges.
Jennifer Marsman is the Principal Engineer of Microsoft’s “AI for Earth” group, where she uses data science, machine learning, and artificial intelligence to aid with clean water, agriculture, biodiversity, and climate change. Jennifer is a frequent speaker at software development conferences around the world. Since 2016, Jennifer was recognized as one of the “top 100 most influential individuals in artificial intelligence and machine learning” by Onalytica, reaching the #2 slot in 2018. She has been featured in Bloomberg for her work using EEG and machine learning to perform lie detection. In 2009, Jennifer was chosen as "Techie whose innovation will have the biggest impact" by X-OLOGY for her work with GiveCamps, a weekend-long event where developers code for charity. She has also received many honors from Microsoft, including the “Best in Role” award for Technical Evangelism, Central Region Top Contributor Award, Heartland District Top Contributor Award, DPE Community Evangelist Award, CPE Champion Award, MSUS Diversity & Inclusion Award, Gold Club, and Platinum Club. Previously, Jennifer was a software developer in Microsoft’s Natural Interactive Services division. In this role, she earned multiple patents for her work in search and data mining algorithms. Jennifer has also held positions with Ford Motor Company, National Instruments, and Soar Technology. Jennifer holds a Bachelor’s Degree in Computer Engineering and Master’s Degree in Computer Science and Engineering from the University of Michigan in Ann Arbor. Her graduate work specialized in artificial intelligence and computational theory.