Instructors for this course
Dr. Amy McGovern
is a Lloyd G. and Joyce Austin Presidential Professor at the University of Oklahoma where she has a dual-appointment in the School of Computer Science and the School of Meteorology. Dr. McGovern earned her PhD. in Computer Science from the University of Massachusetts Amherst and her B.S. (honors) in Math/Computer Science from Carnegie Mellon University.
Dr. McGovern’s research focuses on developing and applying AI techniques to a variety of real-world applications, with a special focus on severe weather.
Dr. Imme Ebert-Uphoff
is a Research Professor in the Department of Electrical and Computer Engineering and the Machine Learning Lead at the Cooperative Institute for Research in the Atmosphere (CIRA), both at Colorado State University. Dr. Ebert-Uphoff received M.S. and Ph.D. degrees in Mechanical Engineering from the Johns Hopkins University in Baltimore, MD, and the equivalent of B.S. and M.S. degrees in mathematics from the University of Karlsruhe, Germany (now known as KIT).
Dr. Ebert-Uphoff’s research focuses on the use of data science methods, including causal discovery and machine learning, to applications in climate and weather.
Dr. Andrew Fagg
is the Brian E. and Sandra O’Brien Presidential Professor of Computer Science, an Associate Professor of Computer Science, and a member of the Institute for Biomedical Engineering, Science and Technology (IBEST) at the University of Oklahoma. He holds a PhD and MS in Computer Science from the University of Southern California and a BS in Math/Computer Science from Carnegie-Mellon University.
Dr. Fagg’s research interests include machine learning, robotics and computational neuroscience. In particular, he employs machine learning techniques to connect brain imaging data with complex motor behavior and to identify changes in each due to development and learning.
Dr. David John Gagne
is a Machine Learning Scientist and head of the Analytics and Integrative Machine Learning group at the National Center for Atmospheric Research. He has led the development of multiple interactive short courses on machine learning for atmospheric science. Dr. Gagne received his Ph.D., M.S., and B.S. in meteorology from the University of Oklahoma.
Dr. Gagne’s research focuses on developing explainable AI systems for a wide range of Earth System Science challenges, including predicting high impact weather and emulating computationally demanding physical models.
