José Ignacio Orlando

José Ignacio Orlando

Assistant Researcher

CONICET

Yatiris - Pladema / UNICEN

Biography

Hi there! I’m José Ignacio Orlando, but everyone call me Nacho :)

I’m an Assistant Researcher at CONICET, working as part of Yatiris lab at Pladema Institute in Tandil, Argentina. I’m also Director of the AI Labs at Arionkoder, as part of a CONICET STAN. Furthermore, I’m actively collaborating with the Vienna Reading Center from the Medical University of Vienna, Austria.

My research interests include machine learning and computer vision techniques for medical imaging applications, mostly centered in ophthalmology.

Apart from PLADEMA (where I did my PhD from 2013 to 2017), my previous affiliations include the Center for Learning and Visual Computing in Paris, France (2013, 6 months working as an intern funded by INRIA), ESAT-PSI in KU Leuven, Belgium (2016, 1 month working as a visiting scholar) and the Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA) from the Medical University of Vienna, Austria (2018-2019, almost 2 years working as a postdoctoral researcher).

Interests
  • Machine/Deep Learning
  • Computer Vision
  • Ophthalmology
Education
  • PhD in Computational and Industrial Mathematics, 2017

    UNICEN

  • Software Engineer, 2013

    UNICEN

Publications

Although I try to keep this list updated, you better check my Google Scholar profile for a full list

Quickly discover relevant content by filtering publications.
NORHA: A NORmal Hippocampal Asymmetry deviation index based on one-class novelty detection and 3D shape features. In Brain Topogr., 2023.

PDF Cite Project

A ResNet is All You Need? Modeling A Strong Baseline for Detecting Referable Diabetic Retinopathy in Fundus Images. In SIPAIM, 2022.

PDF Cite Dataset Project

A deep learning model for brain vessel segmentation\ in 3DRA with arteriovenous malformations. In SIPAIM, 2022.

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Assessing Coarse-to-Fine Deep Learning Models for Optic Disc and Cup Segmentation in Fundus Images. In SIPAIM, 2022.

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Linking Function and Structure with ReSenseNet: Predicting Retinal Sensitivity from Optical Coherence Tomography using Deep Learning. In Ophthalmol Retina, 2022.

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Teaching

These are all the courses in which I worked / I’m working on, either as a Teaching Assistant or as a Professor in charge.

Diplomatura Universitaria en Inteligencia Artificial (DUIA).

Professor in:

  • Machine Learning (Aprendizaje de Máquinas)
  • Computer Vision with Artificial Intelligence (Visión Computacional basada en Inteligencia Artificial)
Tecnicatura Universitaria en Desarrollo de Aplicaciones Informáticas (TUDAI).

Teaching Assistant in:

  • Workshop in Computational Mathematics (Taller de Matemática Computacional). 2015-2017.
Software Engineering (Ingeniería de Sistemas)

Teaching Assistant in:

  • Information Theory (Teoría de la Información). 2013-2015, 2020-Present.
  • Medical Imaging Workshop (Taller de Imágenes Médicas). 2015-2017.
  • Software Development Methodologies (Metodologías de Desarrollo de Software). 2010-2013. Ad-honorem.

Supervision

Students and Researchers I’ve supervised

Tomás Castilla.

Advisor: José Ignacio Orlando. Programa de Fortalecimiento a la Ciencia y la Tecnología en las Universidades Nacionales. SECAT, UNICEN.

Topic: Deep learning algorithms for computer assisted diagnostic of diabetic retinopathy from fundus pictures.

Francisco Iarussi.

Advisor: Ignacio Larrabide. Co-advisor: José Ignacio Orlando. Consejo Interuniversitario Nacional (CIN).

Topic: DeepBrain: Machine Learning applied to study brain morphological alterations in MRI scans.

Lautaro Gramuglia.

Advisors: José Ignacio Orlando, Carlos A. Bulant. Facultad de Ciencias Exactas, UNICEN.

Topic: Artery/Vein classification from color fundus photographs for blood flow simulations.

Rodrigo Cobo.

Advisors: José Ignacio Orlando, Ignacio Larrabide. Facultad de Ciencias Exactas, UNICEN.

Topic: Stereoscopic camera simulation using neural networks.

Santiago Vitale.

Advisor: Ignacio Larrabide. Co-advisor: José Ignacio Orlando.

Topic: Unpaired generative adversarial models for realistic abdominal ultrasound simulation.

Ariel Borthiry and Mauro Giamberardino.

Advisors: José Ignacio Orlando, Mariana del Fresno. Facultad de Ciencias Exactas, UNICEN.

Topic: Retinal blood vessel segmentation in ultra-wise field of view angiographies. Finished with grade 10/10.

Marcos Fracchia and Valeria del Río.

Advisors: José Ignacio Orlando, Mariana del Fresno. Facultad de Ciencias Exactas, UNICEN.

Topic: Feature engineering for retinal blood vessel segmentation in fundus images. Finished with grade 10/10.

Manuel Corrales and Carmen Escudero Leoz.

Advisors: José Ignacio Orlando, Mariana del Fresno. Facultad de Ciencias Exactas, UNICEN.

Topic: Integrating fuzzy C-means and deformable models for 3D medical image segmentation. Finished with grade 10/10.

Experience

 
 
 
 
 
Assistant Researcher
Nov 2019 – Present Tandil, Argentina

Research project: retinAR: computing and discovering retinal disease biomarkers from fundus images using deep learning

Responsibilities include:

  • Conducting research on retinal image analysis with deep learning
  • Modelling AI solutions for ophthalmology problems
  • Supervising PhD & undergrad students
 
 
 
 
 
Postdoctoral Research Fellow
Sep 2019 – Oct 2019 Tandil, Argentina

Research project: retinAR: computing and discovering retinal disease biomarkers from fundus images using deep learning

Responsibilities include:

  • Conducting research on retinal image analysis with deep learning
 
 
 
 
 
Postdoctoral Research Fellow
Jan 2019 – Aug 2019 Vienna, Austria

Research project: Deep learning for retinal OCT image analysis

Responsibilities include:

  • Conducting research on photoreceptor segmentation in OCT images using deep learning
  • Collaborating with colleagues from the lab in other retinal imaging projects
  • Collaborating with Anna Breger and Martin Ehler from University of Vienna
 
 
 
 
 
Visiting Scholar
Oct 2016 – Oct 2016 Tandil, Argentina

Research project: Red lesion detection in fundus photographs

Responsibilities include:

  • Presenting ungoing research to ESAT-PSI staff.
  • Closing a publication.
 
 
 
 
 
Intern
May 2013 – Nov 2013 Paris, France

Research project: Retinal image analysis with machine learning. Supervisor: Prof. Matthew B. Blaschko (INRIA)

Responsibilities include:

  • Developing a machine learning algorithm for retinal vessel segmentation in fundus images
 
 
 
 
 
Doctoral Research Fellow
Apr 2013 – Dec 2017 Tandil, Argentina

Research project: Machine learning for ophthalmic screening and diagnostics from fundus images

Supervisors: Prof. Matthew B. Blaschko (KU Leuven) & Prof. Mariana del Fresno (UNICEN)

Contact