AI for Good Seminar Series: AI for Earth and the Environment
January 27, 2020 - 4:30pm
Hewlett Teaching Center, Room 200
How can AI and machine learning be leveraged to mitigate the impact of human activities on earth’s natural systems? Learn about data science tools and strategies being used to safeguard our water supply, feed the worldwide human population, and promote greater biodiversity and global sustainability.
Lucas Joppa, Chief Environmental Officer, Microsoft
As Microsoft’s first Chief Environmental Officer, Dr. Lucas Joppa works to advance the company’s core commitment to sustainability through technology innovation, program development, policy advancement, and global operational excellence. With a background in both environmental science and data science, Lucas is committed to using the power of advanced technology to help transform how society monitors, models, and ultimately manages Earth’s natural resources. Dr. Joppa founded Microsoft’s AI for Earth program in 2017—a five-year, $50 million cross-company effort dedicated to delivering technology-enabled solutions to global environmental challenges. Previously, Lucas was Microsoft’s Chief Environmental Scientist and led research programs in Microsoft Research. He remains an active scientist and one of Microsoft’s foremost AI thought leaders, speaking frequently on issues related to Artificial Intelligence, environmental science, and sustainability. With extensive publication in leading academic journals, such as Science and Nature, Dr. Joppa is a uniquely accredited voice for sustainability in the tech industry. He holds a PhD in Ecology from Duke University , a BS in Wildlife Ecology from the University of Wisconsin, and is a former Peace Corps volunteer to Malawi.
Stefano Ermon, Assistant Professor of Computer Science, Stanford University
Dr. Ermon is an Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory and is a fellow of the Woods Institute for the Environment. His research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. Dr. Ermon received his PhD from Cornell University.
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