Oct. 5 researcher panel to discuss AI for predictive science

UNIVERSITY PARK, Pa. — Artificial intelligence is affecting society worldwide, from improving medical diagnostic tools, to bolstering supply chains and refining weather forecasting, along with many more applications. Closer to home, Penn State researchers are also leveraging AI techniques in their work to advance their science.

The Institute for Computational and Data Sciences (ICDS), which supports Penn State researchers using advanced research computing techniques, including AI, is bringing together a group of Penn State researchers to discuss their work using AI for predictive modeling and analytics, as well as the ethical considerations of AI. The panel, “AI for Predictive Science,” will be held online at 2 p.m. on Monday, Oct. 5. The event is free and open to the public, and advance registration is required.

"Predictive science methods and solutions are generally ensconced in existing algorithms and software based on sound physics, mathematics and statistics. However, they often lag behind the revolution in computational power and artificial intelligence and machine learning. There is a potential transformative solution to this problem by leveraging recent advances in big data analytics," said Guido Cervone, professor of geography and meteorology and atmospheric science, and ICDS associate director, who will moderate the panel. "This panel will discuss AI/ML within the context of making future predictions, giving the perspective of several colleagues who are active in this field.  Furthermore, it will give the opportunity to participate in ICDS activity to catalyze resources and expertise for future initiatives."

The panel will include four researchers: David Hughes, associate professor of entomology and biology; David Hunter, professor of statistics; Chaopeng Shen, associate professor of civil and environmental engineering; and Jian Sun, postdoctoral scholar in the College of Earth and Mineral Sciences. Hunter plans to discuss the ethical considerations of AI by sharing his experience related to a court case that went before the U.S. Supreme Court. The other panelists will discuss their work with developing and using AI tools.

Hughes is the founder of PlantVillage, an AI first platform that helps smallholder farmers in developing countries. PlantVillage has an AI assistant called Nuru (Swahili for ‘light’) that has three components to its artificial intelligence: human expert-level crop-disease diagnostics using computer vision; above-human capabilities in anomaly detection and forecasting based on ground- and satellite-derived data; human language comprehension, and automated responses to questions posed by African farmers. All three of Nuru’s components are powered by recent advances made in the field of deep learning, including convolutional neural networks, recurrent neural networks and Transformer networks, respectively. Nuru is used by smallholder farmers, which has led to behavioral change and improved climate-change adaptation. It also powers knowledge delivery to 9 million farmers weekly in Kenya through a partnership with the United Nations.

Shen’s research uses deep learning, a form of AI, to investigate the interactions between hydrology and other Earth systems, such as carbon cycles. The team hopes to use this work to better characterize the ways that scarce or excess water availability impacts different parts of the natural world and society. His group received a Google AI Impact grant to develop a tool to forecast landslides using AI and also has focused on developing deep learning approaches to predict soil moisture. The tools his team have be used for predictive analytics in a variety of applications.

Sun works with multiple research groups in the College of Earth and Mineral Sciences, including Cervone’s, as well as groups led by Christelle Wauthier, associate professor of geosciences and ICDS Faculty Fellow, and Melissa Gervais, assistant professor of meteorology and atmospheric science. Sun develops and applies AI techniques for a variety from applications, from improving climate modeling to forecasting wind energy availability to improving ground movement prediction related to volcanic activity.

Last Updated October 06, 2020