There are many problems in ecological science and ecosystem management that could be transformed by machine learning. This talk will give an overview of several research projects at Oregon State University in this area and discuss the novel machine learning problems that arise. These include (a) automated data cleaning and anomaly detection in sensor data streams, (b) species distribution modeling including modeling of bird migration from citizen science data, and (c) design of optimal policies for managing wildfires and invasive species. The machine learning challenges include flexible anomaly detection for multiple data streams, explicit models of sampling bias and measurement processes, combining probabilistic graphical models with non-parametric learning methods, and optimization of complex spatio-temporal Markov processes.

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.