“Phenotypic cancer imaging signatures towards precision cancer screening”

Background: I received my Ph.D. in Biomedical Engineering from the National Technical University of Athens in 2014, part of which was performed in collaboration with the Ecole Centrale de Paris. I recently also received my Clinical Research Certificate from UPenn for training in clinical epidemiology, biostatistics and translational research My graduate research focused on discovering risk imaging biomarkers for assessing the vulnerability of atherosclerotic lesions in carotid arteries. As a postdoctoral researcher at UPenn, my research focus has been on quantitative imaging phenotypes, pattern recognition and deep learning in the context of breast tissue characterization and breast cancer risk. Over the course of my research activity, I have been involved in four funded research projects, and I have co-authored 44 peer-reviewed publications and 2 book chapters related to computational image analysis and machine learning. Moreover, I am currently leading a Susan G. Komen postdoctoral fellowship grant aiming to advance imaging phenotyping of breast cancer risk via cutting-edge deep learning technologies.

Hosted by the Computational Imaging Lab (CIL) (formerly the Electronic Radiology Lab (ERL)).

For inquiries contact Cathy Gezella.