CRCD: Machine Learning: A Multidisciplinary Computer Engineering Graduate Program

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EIA 9980296Wunsch, Donald Dunyak, James P.Feldkamp, Lee A.Texas Tech UniversityCRCD: Machine Learning: A Multi-disciplinary Computer Engineering Graduate ProgramThis CISE Combined Research-Curriculum Development proposal requests funds to develop a machine learning track in Computer Engineering M.S. and Ph.D. programs. The machine learning track will be interdisciplinary and will include three new courses at the senior undergraduate/graduate level: Advanced Neural Networks (CS), Dynamic Programming (Math), and Adaptive Critic Designs (EE). The new courses will include interaction with leading industrial researchers through distance learning. In addition to the new courses, there will be four laboratory rotations: Computational Intelligence Laboratory (EE), Industrial Applications Laboratory (EE), Applied Probability Laboratory (Math), and Software Engineering Laboratory (CS). For the laboratory rotation courses, the students will be organized in teams and directed towards real research problems with direct industrial relevance. As a capstone experience, students will participate in a one-semester internship at a national laboratory or industrial facility. The PI's will concurrently be developing a textbook on Adaptive Critic Designs. This project has the potential to have a significant impact. It could serve as a model for the design of new interdisciplinary degree programs at other institutions.