A Cornell-led collaboration used machine learning to pinpoint the most accurate means, and timelines, for anticipating the advancement of Alzheimer’s disease. Read more about Machine learning gives nuanced view of Alzheimer’s stages
Mert R. Sabuncu joined Cornell University in July 2017 as Assistant Professor in the School of Electrical and Computer Engineering, with a secondary appointment in the School of Biomedical Engineering.
Dr. Sabuncu received a Ph.D. degree in Electrical Engineering from Princeton University, where his dissertation work focused on entropy-based image registration. He then moved to Massachusetts Institute of Technology (MIT) to do a post-doc at the Computer Science and Artificial Intelligence Lab (CSAIL). His post-doc work dealt with developing algorithms to analyze large-scale biomedical image data.
- Biomedical image analysis, with application focus in neurology/neuroscience
- Applied machine learning in bio-medicine
- Probabilistic modeling of biological (e.g., genetic) data
- Image processing, computer vision.
- Artificial Intelligence
- Computer Aided Diagnosis
- Image Analysis
- Signal and Image Processing
- Statistics and Machine Learning
- Biomedical Engineering
- Biomedical Imaging and Instrumentation
- Computational Science and Engineering
- Systems and Synthetic Biology
- Systems and Networking
- Bio-Electrical Engineering
- Information Theory and Communications
- Information, Networks, and Decision Systems
- Ge, T., M. Reuter, A. M. Winkler, A. J. Holmes, P. H. Lee, L. S. Tirrell, Mert Sabuncu. 2016. "Multidimensional heritability of neuroanatomical shape." Nature communications.
- Sabuncu, Mert, E. Konukoglu. 2015. "Clinical prediction from structural brain MRI scans: a large-scale empirical study. "Neuroinformatics 13 (1).
- Sabuncu, Mert, B. T. Yeo, K. Van Leemput, B. Fischl, P. Golland. 2010. "A generative model for image segmentation based on label fusion." IEEE transactions on medical imaging 29 (10).
- Sabuncu, Mert, B. D. Singer, B. Conroy, R. E. Bryan, P. J. Ramadge, J. V. Haxby. 2010. "Function-based intersubject alignment of human cortical anatomy." Cerebral Cortex 20 (1).
Selected Awards and Honors
- Michael Tien '72 Sustained Excellence & Innovation in Engineering Education Award 2021
- Young Investigator Publication Impact Award (Co-authored paper) (MICCAI'11) 2011
- Career Development Grant (K25) (NIH NIBIB) 2011
- Catalyst KL2 Merit Award (Harvard) 2010
- Outstanding Teaching Assistant Award (Department of Electrical Engineering, Princeton University) 2006
- B.S. (Electrical and Electronic Engineering), Middle East Technical University, 2001
- M.Eng. (Electrical Engineering), Princeton University, 2003
- Ph.D. (Electrical Engineering), Princeton University, 2006