José Ignacio Orlando

José Ignacio Orlando

Assistant Researcher


Yatiris - Pladema / UNICEN


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

I’m an Associate 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. You can learn more about what we do in Arionkoder in this link.

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).

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


  • Software Engineer, 2013



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.
Anomaly guided segmentation: Introducing semantic context for lesion segmentation in retinal OCT using weak context supervision from anomaly detection. In MedIA, 2024.


Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation. In Sci Data, 2024.

PDF Cite Code Dataset DOI

GAMMA challenge: Glaucoma grAding from Multi-Modality imAges. In MedIA, 2023.


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


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

Maestría en Explotación de Datos y Descubrimiento de Conocimiento

Professor in:

  • Computer Vision based on Artificial Neural Networks
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.


Students and Researchers I’ve supervised

Franco Arellano.

Advisor: José Ignacio Orlando.

Topic: Web scraping of images with anomaly detection based filtering.

Leandro Rocamora.

Advisor: José Ignacio Orlando.

Topic: Implantable collamer lens sizing with machine learning models

Lucas Telesco.

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

Topic: Deep learning tools for assisting screening of retinal diseases

Eugenia Moris.

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

Topic: Machine learning methods for biomedical signal analysis

Duilio Deangeli.

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

Topic: Characterization of normal asymmetries in homologous brain structures

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.


Director of AI Labs
Apr 2023 – Present Boston, United States

General coordination and supervision of all the AI initiatives of the company.

Responsibilities include:

  • Meeting with customers and prospects to determine the scope and requirements of their AI projects.
  • Modelling AI solutions for customers’ scenarios.
  • Coordinating the AI labs, including supervising ML Engineers, Data Engineers and Scientists.
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.
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)