About me
I am a PhD Machine Learning Engineer and Researcher from Argentina, specialized in the field of computer vision, graph neural networks, and deep learning.
In May 2020, I received my Computer Engineer degree from the Facultad de Ingeniería y Ciencias Hídricas at the Universidad Nacional del Litoral (UNL), Santa Fe, Argentina. Upon completion, I secured a CONICET scholarship to embark on my PhD journey at the same university. On February 2024, after almost 4 intense years, I got my PhD in Engineering degree!
My PhD’s work was based at sinc(i), the Research Institute for Signals, Systems and Computational Intelligence. There, I worked under the direct supervision of Enzo Ferrante, contributing to cutting-edge developments in our field. My research often intersects with medical imaging, with key projects focusing on advanced segmentation techniques and leveraging deep learning for high throughput phenotyping of plant roots.
Latest News
14 February 2024: I defended my PhD Thesis, “Nuevos métodos de aprendizaje profundo para la extracción de grafos a partir de imágenes” (Novel deep learning methods for image to graph extraction)! I got my PhD degree in Engineering: Signals, Systems and Artificial Intelligence.
January 2024: I left Santa Fe, and now I’m living in Buenos Aires!
22 November 2023: Our latest paper “Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI”, born from the colaboration with the Center for Computational Imaging & Simulation Technologies in Biomedicine, CISTIB, is now available on arXiv.
1st September 2023: Our paper “Unsupervised bias discovery in medical image segmentation”, accepted for publication at Fairness in AI in Medical Imaging - MICCAI 2023 Workshop, is now available on arXiv.
27 August 2023: Our HybridGNet model for Chest X-ray segmentation is now publicly available on a HuggingFace Space! Check it out here.
7 July 2023: We released the CheXmask Dataset, a large-scale dataset of anatomical segmentation masks for more than 650.000 multi-center chest x-ray images with both physician and automatic quality validation. The dataset is available at PhysioNet. Check the paper on arXiv!
18-23 June 2023: Assisted the International Conference on Information Processing in Medical Imaging (IPMI 2023) in San Carlos de Bariloche, Argentina as a volunteer for the organization.
6-10 March 2023: Presented my work on “HybridGNet: Leveraging graph-based representations of organs for anatomically plausible medical image segmentation” at Khipu: Latin American Meeting In Artificial Intelligence in Montevideo, Uruguay in a poster presentation.
22 January 2023: Our latest work, “Multi-center anatomical segmentation with heterogeneous labels via landmark-based models”, was accepted for publication at ISBI 2023.
24 November 2022: Our research titled “Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis” was published online in the IEEE Transactions on Medical Imaging.
1 November 2022: Concluded a productive research period at the Institute of Plant Sciences Paris-Saclay (IPS2).
26 October 2022: Delivered a seminar at IPS2, Université Paris-Saclay, discussing “ChronoRoot: high throughput phenotyping of plant roots using deep learning”.
25 October 2022: Presented a seminar at CentralSupélec, Université Paris-Saclay. The presentation, titled “Translating images into graphs: novel computer vision methods for extracting graphs from images,” introduced novel methods for converting images to graph structures.
30 September 2022: Arrived in Paris to begin my research visit at the Institute of Plant Sciences Paris-Saclay (IPS2).
25 August 2022: Commenced teaching “Linear Algebra, Optimization and Machine Learning” at FIQ, UNL.
02 August 2022: Completed my time at CISTIB, contributing to the Centre for Computational Imaging & Simulation Technologies in Biomedicine.
15 July 2022: Visited the Centre for Medical Image Computing (CMIC) at UCL, marking the conclusion of my time at the UCL Medical Image Computing Summer School (MedICSS).
11 – 15 July 2022: Attended the UCL Medical Image Computing Summer School (MedICSS). Our group project on devising a deep learning pipeline for retinal image analysis earned a spot in the Top 3.
1 July 2022: Joined the Center for Computational Imaging & Simulation Technologies in Biomedicine, CISTIB, at Leeds University for an exciting new research opportunity.
19 - 24 June 2022: Virtually participated in CVPR 22, benefiting from a free registration and travel award granted by the conference. Unfortunately, visa restrictions prevented me from attending in person.