Enzo Ferrante

CONICET Research Scientist


About me

I'm currently a CONICET researcher 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. 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.

As an intern, I worked at several research institutes. During 2010, I was an intern at STEEP Team (INRIA Grenoble, France) working on transport/land-use mathematical modeling. In 2011, I did my engineering thesis at Pladema Institute (UNICEN University, Tandil, Argentina) about active contour models for brain tumor segmentation. 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.

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

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.