Uxía Veleiro

I am pursuing a Ph.D. in Graph Neural Networks for Drug Repurposing in the In the Machine Learning in Biomedicine research group at Cima University of Navarra .

Before joining Cima, I earned a Master’s in Quantitative Biotechnology at BIFI, University of Zaragoza (2021). I also hold a Degree in Physics from the University of Santiago de Compostela (2020), including an ERASMUS year at Heidelberg University (2018-2019).

More in-depth on the focus of my doctoral research

In the Machine Learning in Biomedicine research group, I specialize in drug repositioning, particularly exploring the potential of Graph Neural Networks (GNNs) as effective models for this task. My dedication lies in bridging computational techniques with biological insights to contribute innovative solutions in drug repurposing.

In this context, we compare the current state-of-the-art models for DTI prediction, focusing on their advantages and disadvantages, and propose guidelines for their development. This study was published in February 2025 in Nature Machine Intelligence, and you can check it here! 🔎. This work as also accepted as an oral communication at the AI4D3 Workshop of Neurips 2023.

Simultaneously, I developed GeNNius, a Graph Neural Network (GNN) model designed for predicting drug-protein interactions. This approach formulates the problem as a link prediction task, and we focused on its prediction and generalization capabilities. This work was published in Bioinformatics in January 2024. Access the full article here.

From November to February 2025 I did a research stay at the Department of Mathematics and Computer Science, University of Basel🇨🇭, in the SADA Group!

If you’d like to learn more or discuss a potential collaboration, I’d be happy to connect! 📩