CV

Education

Ph.D in Version Control Theory, GitHub University, 2018 (expected)
M.S. in Jekyll, GitHub University, 2014
B.S. in GitHub, GitHub University, 2012

Work experience

Spring 2024: Academic Pages Collaborator
- GitHub University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
Fall 2015: Research Assistant
- GitHub University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Summer 2015: Research Assistant
- GitHub University
- Duties included: Tagging issues
- Supervisor: Professor Git

Skills

Skill 1
Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
Skill 3

Publications

Are generative models fair? A study of racial bias in dermatological image generation

A fusocelular skin dataset with whole slide images for deep learning models

The CrowdGleason dataset: Learning the Gleason grade from crowds and experts

Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset

Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological images

Learning from crowds for automated histopathological image segmentation

An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection

Unsupervised Prediction of Blastocyst Development from Oocyte images

Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset

Crowdsourcing segmentation of histopathological images using annotations provided by medical students

Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification

Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection

Learning from crowds in digital pathology using scalable variational Gaussian processes

A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes

A TV-based image processing framework for blind color deconvolution and classification of histological images

Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor

A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes

Talks

Bayesian generative models can flag performance loss and bias

December 01, 2025

Transversality Applied to Research in Biosciences: Artificial Intelligence, Bionics, and Bioengineering

July 01, 2024

keynote at CEEBI 2024, CEEBI 2024, Student BioScience Conference, Granada

Machine learning meets mathematics

January 01, 2024

keynote at IMAG Workshop 2024, I WorkShop IMAG at UGR

Can machines take intelligent decisions?

April 01, 2023

keynote at UGR Computing History 2023, The Evolution of Computers at the UGR: A Journey Through the History of Computing, Granada

Miguel

CV