Monday October 5 4:00 - 4:50 PM Kelley 1003
Thomas G. Dietterich Professor School of Electrical Engineering and Computer Science Oregon State University Machine Learning in Ecosystem Informatics and Sustainability Ecosystem Informatics brings together mathematical and computational tools to address scientific and policy challenges in the ecosystem sciences. These challenges include novel sensors for collecting data, algorithms for automated data cleaning, learning methods for building statistical models from data and for fitting mechanistic models to data, and algorithms for designing optimal policies for biosphere management. This talk will describe recent work on the first two of these---new devices for automated arthropod population counting and linear Gaussian DBNs for automated cleaning of sensor network data. It will also give examples of open problems along the whole spectrum from sensors to policies. Biography Dr. Dietterich's current research focuses on interdisciplinary research at the boundary of computer science, ecology, and sustainability policy. He is PI (with Carla Gomes of Cornell) of an 5-year NSF Expedition in Computational Sustainability. He is part of the leadership team for OSU's Ecosystem Informatics programs including the Ecosystem Informatics IGERT and the NSF Summer Institute in Ecoinformatics. Dr. Dietterich (AB Oberlin College 1977; MS University of Illinois 1979; PhD Stanford University 1984) is Professor and Director of Intelligent Systems in the School of Electrical Engineering and Computer Science at Oregon State University, where he joined the faculty in 1985. In 1987, he was named a Presidential Young Investigator for the NSF. In 1990, he published, with Dr. Jude Shavlik, the book entitled Readings in Machine Learning, and he also served as the Technical Program Co-Chair of the National Conference on Artificial Intelligence (AAAI-90). From 1992-1998 he held the position of Executive Editor of the journal Machine Learning. The Association for the Advancement of Artificial Intelligence named him a Fellow in 1994, and the Association for Computing Machinery did the same in 2003. In 2000, he co-founded a new, free electronic journal: The Journal of Machine Learning Research and he is currently a member of the Editorial Board. He served as Technical Program Chair of the Neural Information Processing Systems (NIPS) conference in 2000 and General Chair in 2001. He is Past-President of the International Machine Learning Society, a member of the IMLS Board, and he also serves on the Advisory Board of the NIPS Foundation
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