Enzo Ferrante

CONICET Research Scientist


About me

I hold a permenent position as CONICET faculty researcher in Argentina, leading a research line on machine learning methods for biological and medical image analysis at the Research institute for signals, systems and computational intelligence (CONICET / Universidad Nacional del Litoral) in Santa Fe, Argentina. I'm also a professor at Universidad Torcuato Di Tella and Universidad de San Andrés, in Buenos Aires, Argentina. In 2012 I received my Systems Engineering Degree from UNICEN University, Tandil, Argentina. In May 2016, I defended my PhD thesis in Computer Sciences, at the Université Paris-Saclay (CentraleSupeléc / INRIA) in France (Paris) where I worked on deformable registration of multimodal medical images, using graphical models and discrete optimization techniques, under the supervision of Prof. Nikos Paragios. After that, until August 2017, I was a postdoc research associate at Imperial College London (BioMedIA lab), under the supervision of Prof. Ben Glocker working on deep learning and brain image segmentation.

I have also worked at several research institutes around the world. In 2021, I received a Fulbright Fellowship to visit the A. Martinos Center for Biomedical Imaging (Massachusetts General Hospital - Harvard Medical School) in Boston. In 2014, as PhD intern I spend 3 months working on shape understanding for the Computer Vision and Geometry Lab at Stanford University, California, USA. During 2010, I was an intern at STEEP Team (INRIA Grenoble, France) working on transport/land-use mathematical modeling.

Contact email: eferrante (at) sinc (dot) unl (dot) edu (dot) ar || ferrante.enzo (at) gmail (dot) com

Colleagues, friends, master and PhD students with whom I work at the Research Institute for Signals, Systems and Computational Intelligence in Santa Fe city, Argentina.

Video presentations and talks

AI for Good Seminar

November, 2021: Invited talk about "Fairness of machine learning classifiers in medical image analysis" at the AI for Good series organized by International Telecommunication Union.

Responsible AI Seminar @ Technical University of Denmark

November, 2021: Invited talk at the Responsible AI Seminar organized by the Technical University of Denmark about fairness in machine learning for medical image analysis.

Khipu 2021

May, 2021: Invited talk at Khipu 2021 about self-supervised learning in biomedical image analysis, toghether with Yann Lecun and Sandra Avila.

Stanford AIMI Journal Club

August, 2020: Invited talk about our paper "Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis"

MINDS & CIS Seminar, Johns Hopkins University

September, 2020: Invited talk at the seminar organized by the Center for Imaging Science (CIS) and the Mathematical Institute for Data Science (MINDS), Johns Hopkins University. I presented our research line on anatomically plausible medical image segmentation, registration and reconstruction, featuring works from Lucas Mansilla, Agostina Larrazabal and Franco Matzkin.

Giambiagi Winter School 2020

August, 2020: I gave an introductory course to convolutional neural networks at the Giambiagi Winter School, organized by the Physics Department of Universidad de Buenoa Aires, Argentina. Talk in spanish.

Class 1:

Class 2:

Khipu 2019

November, 2019: I was invited as a plenary speaker to the 1st Latin American meeting on Artificial Intelligence, Khipu 2019, organized in Uruguay. My talk was an introduction to convolutional neural networks.


I'm including a list of selected publications, for a full list see my Google Scholar Profile. If you have troubles to access them, please email me.