Bayesian and Machine Learning-Based Methods for Computational Imaging - Mujdat Cetin

The University of Utah Electrical and Computer Engineering department features Mujdat Cetin, a Professor of Electrical and Computer Engineering and the Robin and Tim Wentworth Director of the Goergen Institute for Data Science at the University of Rochester. Cetin is also serving as the Director of the New York State Center of Excellence in Data Science. Mujdat Cetin received his BS in electrical engineering from Bogazici University, Istanbul, Turkey in 1993, an M.S. in electrical engineering from the University of Salford, Manchester UK in 1995, followed by a Ph.D. in electrical engineering from Boston University, Boston, MA in 2001. Professor Cetin’s research interests are within the broad area of data, signal, and imaging sciences, with cross-disciplinary links to several other areas in electrical engineering, computer science, and neuroscience. The overarching theme of his research is the development of probabilistic and machine learning-based methods for robust and efficient information extraction at various levels of abstraction from observed uncertain, complex data. His research group has made advances in three key areas: computational sensing and imaging as applied to radar and biomedical imaging; probabilistic methods for image and video analysis as applied to biomedical image analysis, microscopic neuroimaging, and computer vision; and signal processing and machine learning for brain-computer/machine interfaces, with applications for alternative communication and rehabilitation for patients and monitoring of cognitive states. Learn more here: http://www.hajim.rochester.edu/ece/people/faculty/cetin_mujdat/