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.