Through books and their images, children learn sociocultural values, correlated with the inclusion and exclusion of people of different racial identities. In this seminar, we will present the data sets we curated and the computer vision methods we applied to children’s books to measure representation, so that decision-makers, push as publishers, can better understand the representation to which they are exposing children.
As a Senior Computational Scientist at The University of Chicago, Teodora engages the community of researchers involved in computational image analysis across multi-disciplinary areas including Biology, Physics, Chemistry, Economics, Public Policy, and Cancer Research.
She serves as a catalyst for solving challenging questions in the research teams that she is supporting, such as: predicting oxygen support for COVID-19 patients, detecting prostate cancer, and analysis of messages related to identity in official educational setting.
Teodora brings to the field practical expertise in state-of-the-art advanced technology: Supercomputers, Cloud Computing, Machine Learning, Image Analysis Techniques, and Big Data. Prior to joining RCC, Teodora earned her doctorate degree in Computer Science at Toulouse University in France. She won international challenges (IUS PICMUS 2016) in beamforming for ultrasound medical imaging.
