Prof. María Rodríguez Martínez is an Associate Professor of Biomedical Informatics & Data Science at Yale School of Medicine and a member of the Center for Systems and Engineering Immunology. Her research lies at the intersection of artificial intelligence and immunology, where she develops interpretable and generative deep learning approaches to model adaptive immune receptors. She integrates deep learning for protein modeling, including protein language models and structure prediction, 0opoppwith experimental data such as high-throughput immune repertoire sequencing and multi-modal datasets to decode sequence-structure-function relationships in T and B cell receptors. Her work has applications in autoimmune disease, vaccine design, and next-generation immunotherapies. Before joining Yale, María spent a decade at IBM Research–Europe, where she led the Computational Systems Biology team and coordinated large interdisciplinary consortia, including EU-funded initiatives to advance personalized cancer medicine through computational modeling. Her leadership in these projects brought together academic, clinical, and industry partners and resulted in high-impact publications and open-source tools adopted across the community. María’s academic career spans physics and systems biology. She has published widely on machine learning for computational biology, immune repertoire dynamics, and structure-based prediction of biomolecular interactions. Her work bridges computational biology, machine learning, and interpretability with a focus on immunological discovery, enhancing reproducibility and accelerating translational impact. As an editorial board member, she contributes expertise in AI-driven method development and evaluation, interdisciplinary peer review, and strategic guidance on emerging computational approaches in biomedicine.
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