Responsible AI Seminar: Enzo Ferrante

On November 5, Enzo Ferrante from CONCET, Argentina, will give a talk.

TitlePortrait of Enzo Ferrante

Gender bias in X-ray classifiers for computer-assisted diagnosis


Medical institutions around the world are adopting machine learning (ML) systems to assist in analyzing health data; at the same time, the fairness research community has shown that ML systems can be biased, resulting in disparate performance for specific subpopulations. In this talk, we will discuss the relationship between bias, ML, and health systems, addressing the specific case of gender bias in X-ray classifiers for computer-assisted diagnosis.

Dr. Ferrante received his Systems Engineering degree from UNICEN University (Argentina), completed his PhD in Computer Sciences at Université Paris-Saclay and INRIA in Paris, France, and worked as a postdoctoral researcher at Imperial College London in the UK. He returned to Argentina in 2017, where he holds a permanent researcher position from the Argentina's National Research Council (CONICET). He leads the Machine Learning for Biomedical Image Computing research line in the Research Institute for Signals, Systems and Computational Intelligence, sinc(i). In 2020 Dr. Ferrante received the Young Researcher Award from the National Academy of Sciences of Argentina, and the Mercosur Science & Technology Award for his scientific contributions in the area of AI for medical image computing. His research interests span both artificial intelligence and biomedical image analysis, with a focus on deep learning methods.

For more details about the talk

This will be a hybrid seminar: you can attend both via Zoom (link above) or physically. Mr. Ferrante will hold his presentation virtually, yet it is also possible (and very much encouraged!) to attend the seminar physically in room 170, DTU building 324. We will have coffee and discussions together before (starting 14:30) and after the talk. If you plan on coming to the physical meeting, please send a brief, informal message to Eike Petersen, so that we can switch to a larger room should it be necessary.

About the Responsible AI Seminar Series

Responsible AI draws on widely different scientific disciplines, from the technical aspects of AI, via ethics, philosophy and law, to the individual realities of different application domains. We wish to take advantage of the limitations imposed by Covid-19 to start an informal conversation across Denmark about different aspects of Responsible AI via a hybrid format seminar series. We hope to catch your interest with three seminar talks before the summer vacation, following which we hope to merge efforts across universities to start a truly inter-university seminar series. Initiators: Aasa Feragen, Melanie Ganz and Sune Hannibal Holm from the DFF-funded project Bias and Fairness in Medicine.

Learn more about the Responsible AI Seminars here.