Mujdat Cetin

Mujdat Cetin

  • Professor of Electrical and Computer Engineering
  • Professor of Computer Science
  • Robin and Tim Wentworth Director, Goergen Institute for Data Science
  • Director, New York State Center of Excellence in Data Science

PhD, Boston University, 2001

1211 Wegmans Hall and 719 Computer Studies Building
(585) 276-5061
mujdat.cetin@rochester.edu


Short Biography

Mujdat Cetin is 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. He is also serving as the Director of the New York State Center of Excellence in Data Science. Previously he served as a faculty member at Sabanci University, Istanbul, Turkey, and as a Research Scientist at MIT. He also held visiting faculty positions at MIT, Northeastern University, and Boston University.

Mujdat Cetin received his BS in electrical engineering from Bogazici University, Istanbul, Turkey in 1993, a MS in electrical engineering from the University of Salford, Manchester UK in 1995, followed by a PhD in electrical engineering from Boston University, Boston, MA in 2001.

Professor Cetin received several awards including the IEEE Signal Processing Society Best Paper Award; the EURASIP/Elsevier Signal Processing Best Paper Award; the IET Radar, Sonar and Navigation Premium Award; and the Turkish Academy of Sciences Distinguished Young Scientist Award.

Professor Cetin is a Fellow of the IEEE and served as a member of the IEEE Signal Processing Society Technical Directions Board and as the Chair of the IEEE Computational Imaging Technical Committee. He is currently a Senior Area Editor for the IEEE Transactions on Computational Imaging and the IEEE Transactions on Image Processing, as well as an Associate Editor for the SIAM Journal on Imaging Sciences. He has been an Associate Editor for the IEEE Transactions on Computational Imaging the IEEE Transactions on Image Processing, the IEEE Signal Processing Letters, and the IEEE Transactions on Cybernetics; a Guest Editor for Pattern Recognition Letters; and an Area Editor for the Journal of Advances in Information Fusion. He has also served as a member of the IEEE Image, Video, and Multidimensional Signal Processing Technical Committee and the IEEE Bioimaging and Signal Processing Technical Committee.

Professor Cetin was the Technical Program Co-chair for the IEEE Image, Video, and Multidimensional Signal Processing (IVMSP) Workshop in 2016; for the International Conference on Information Fusion in 2016 and 2013; for the International Conference on Pattern Recognition (ICPR) in 2010; and for the IEEE Turkish Conference on Signal Processing, Communications, and their Applications in 2006. He was one of the keynote speakers for the 2015 International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing. He served as an Area Chair for the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) and for the IEEE International Conference on Image Processing (ICIP) multiple times.


Research Overview

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.

For Professor Cetin’s publications, please see his Google Scholar profile.

Research Overview

Research Interests

  • 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
  • signal processing and machine learning for brain-computer/machine interfaces, with applications for alternative communication and rehabilitation for patients and monitoring of cognitive states