Skip to main content

Ipek Oguz

Assistant Professor of Computer Science


Electrical Engineering and Computer Science


Intellectual Neighborhoods

Research Focus

I work on creating new methods for medical image analysis. My technical expertise and interests are focused on graph theoretic techniques for structural image analysis with particular emphasis on longitudinal imaging studies and machine learning. My method development work in these areas is driven by biological problems in three application domains: neuroimaging, ophthalmic imaging, and obstetric imaging. 


Biography

Ipek Oguz is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Vanderbilt University. She received her Ph.D. in Computer Science at the University of North Carolina at Chapel Hill. Prior to joining Vanderbilt, she worked in the Penn Image Computing and Science Laboratory (PICSL) and Center for Biomedical Image Computing and Analytics (CBICA) at the University of Pennsylvania as well as in the Iowa Institute for Biomedical Imaging (IIBI) at the University of Iowa. Her research is in the field of medical image analysis and specifically in the development of novel methodology for quantitative medical image analysis, with applications to neuroimaging, including Huntington’s disease and multiple sclerosis, as well as ophthalmic and obstetric imaging. Her technical interests include graph-based segmentation methods, longitudinal studies and machine learning. She has co-authored more than 50 peer-reviewed journal and conference publications. She is an executive in the Women in MICCAI Committee and a co-chair of IPMI 2017.