Publications
Publications
The full, always up-to-date list lives on Google Scholar.
Google Scholar profile
Papers, citations and co-authors.
13,171Citations
35h-index
59i10-index
As of October 2026.
Open Google Scholar →Selected papers
A selection of recent and representative work.
NeurIPS 2026 (in press)FOCUS: Benchmarking Retinal Model Generalization from Foundation Vision Encoders to Multimodal LLMs
EMNLP 2026Implicit Bias in LLMs for Transgender Populations
ICLR 2026Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation
IEEE TPAMI 2026Remedying uncertainty representations in visual inference through Explaining-Away Variational Autoencoders
IEEE TMI 2026ConfIC-RCA: Statistically Grounded Efficient Estimation of Segmentation Quality
MIDL 2026CheXmask-U: Quantifying uncertainty in landmark-based anatomical segmentation for X-ray images
WACV 2026PVeRA: Probabilistic Vector-Based Random Matrix Adaptation
GigaScience 2026ChronoRoot 2.0: An open AI-powered platform for 2D temporal plant phenotyping
arXiv 2026On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings
ICLR 2026 · WorkshopInference-Time Toxicity Mitigation in Protein Language Models
ACL 2025Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation
ACM FAccT 2025Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation
ACM FAccT 2025In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review
The BMJ 2025FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Medical Image Analysis 2025Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI
MICCAI 2025 · FAIMI WorkshopFairness and Robustness of CLIP-Based Models for Chest X-rays
MICCAI 2025 · WorkshopOn the risk of misleading reports: diagnosing textual biases in multimodal clinical AI
Computers in Biology and Medicine 2025Towards reliable WMH segmentation under domain shift: an application study using Maximum Entropy Regularization to improve uncertainty estimation
Nature Machine Intelligence 2024Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology
ECCV 2024ViG-Bias: Visually Grounded Bias Discovery and Mitigation
Scientific Data 2024CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images
NeurIPS 2024 · IAI WorkshopSignAttention: On the Interpretability of Transformer Models for Sign Language Translation
MICCAI 2024 · AMAI WorkshopSource Matters: Source Dataset Impact on Model Robustness in Medical Imaging
European Radiology 2024Class imbalance on medical image classification: Towards better evaluation practices for discrimination and calibration performance
MICCAI 2023 · FAIMI WorkshopUnsupervised bias discovery in medical image segmentation
MICCAI 2023 · Best paper shortlistMaximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation
IEEE TPAMI 2023Supervision by Denoising for Medical Image Segmentation
MICCAI 2023 · FAIMI WorkshopTowards unraveling calibration biases in medical image analysis
Book · Vera Cartonera, UNL 2022ES¿Aprendizaje automágico? Un viaje al corazón de la inteligencia artificial contemporánea
Nature Communications 2022Addressing fairness in artificial intelligence for medical imaging
IEEE TMI 2022Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis
ICCV 2021Domain Generalization via Gradient Surgery
MICCAI 2021Hybrid graph convolutional neural networks for landmark-based anatomical segmentation
MICCAI 2021 · OralOrthogonal Ensemble Networks for Biomedical Image Segmentation
PNAS 2020Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
The Lancet Digital Health 2020Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning
IEEE TMI 2020Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders
AutoImplant 2020 · Best Paper AwardCranial Implant Design via Virtual Craniectomy with Shape Priors
Neural Networks 2020Learning deformable registration of medical images with anatomical constraints
MICCAI 2019 · OralAnatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders
Medical Image Analysis 2018Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer’s Disease
IEEE TMI 2017Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
BRATS 2017 · 1st place