CV

Education

• Ph.D in Bioinformatics and Systems Biology, University College Dublin, 2027 (expected)
• M.S. in Bioinformatics, with focus on Protein Structure and Drug Design, Autonomous University of Barcelona 2022
• B.S. in Biotechnology, University of Oviedo, 2021

Work experience

• Jan 2023 - Present: Industrial PhD Student
  • IBM Research and University College Dublin
  • Duties includes: Foundational multimodal models for protein and peptide representation learning. Demonstrator.
  • Supervisor: Prof. Denis Shields and Dr. Thanh Lam Hoang
• Feb 2022 - Dec 2022: Research and Development Assistant
  • Autonomous University of Barcelona (Insilichem research group)
  • Duties included: Developing a 3D CNN model to predict metal diffusion paths in protein structures.
  • Supervisor: Dr. Jean-Didier Maréchal
• Nov 2020 - Jun 2021: Research Assistant (intern)
  • University of Oviedo (BIOMIC research group)
  • Duties included: Experimental work on genetic engineering of a strain of Streptomyces to produce novel bioactive natural products (PCR, CRISPR-Cas9, HPLC, etc.).
  • Supervisor: Prof. Carmen Méndez

Skills

• Autonomous Research
  • Project Management
  • Public Speaking
  • Scientific writing
• Computational Chemistry
  • Molecular Dynamics
  • Docking
  • RDKit
• Bioinformatics
  • Sequence/Structural alignment
  • Protein structural modelling
• Machine learning
  • Protein and Chemical Language Models
  • Graph Neural Networks
  • Out-of-distribution quantification
  • Software engineering

Publications

A new framework for evaluating model out-of-distribution generalisation for the biochemical domain

Fernandez-Diaz R, Lam HT, López V, Shields DC. A new framework for evaluating model out-of-distribution generalisation for the biochemical domain. In The Thirteenth International Conference on Learning Representations.

AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors

Fernández-Díaz R, Cossio-Pérez R, Agoni C, Lam HT, Lopez V, Shields DC. AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors. Bioinformatics. 2024 Sep;40(9):btae555.

Talks

Modelos que aprenden el lenguaje de las moléculas y cómo utilizarlos para predecir sus propiedades.

March 19, 2024

Keynote Talk at University of Alcala de Henares, Alcala de Henares, Spain

Teaching

Models that learn biochemistry

Deep learning in biomedicine - SECUAH IX

Demonstrator Bioinformatics UCD (MEIN30240)

Deep learning in biomedicine - SECUAH VII