Patricia Gonzalez Dias Carvalho
Post-Doctoral Research Associate In Computational Biology
Computational Biologist | Systems Vaccinology | Explainable AI
Patricia holds an MSc in Cellular and Molecular Biology from the Oswaldo Cruz Institute (Fiocruz, Brazil) and a PhD in Pathophysiology and Toxicology from the University of São Paulo.
During her master's research, she investigated immune responses induced by different vaccine adjuvants and their application to the development of subunit vaccines in preclinical models. During her PhD, she transitioned into computational biology, applying systems biology approaches to understand host immune responses to vaccination.
Her research integrates immunomics, transcriptomics, clinical, and reactogenicity data using systems biology, machine learning, and explainable artificial intelligence (XAI) to identify molecular and immune signatures associated with vaccine- and infection-induced immunity. Her work aims to advance precision vaccinology by decoding the mechanisms underlying inter-individual variability in immune responses.
Patricia joined the Oxford Vaccine Group in 2022 as a Postdoctoral Research Associate in Computational Biology. Her research focused on respiratory infectious diseases using data from the Experimental Human Challenge Platform, with a particular emphasis on identifying immune correlates of protection against pneumococcal infection.
From July 2026, Patricia will establish her own research group at Instituto Butantan, where she will lead the programme "Decoding Host-Specific Vaccine Responses: A Systems Biology and Explainable AI Framework for Translational Immunology." Her research will focus on developing computational frameworks to identify predictive biomarkers of vaccine efficacy, understand the biological mechanisms driving heterogeneous immune responses, and accelerate the design of next-generation vaccines through data-driven translational immunology.
Recent publications
Machine learning-driven identification of serotype-independent pneumococcal vaccine candidates using samples from human infection challenge studies.
Journal article
Cheliotis KS. et al, (2026), Vaccine, 75
The effect of pneumococcal conjugate vaccine and pneumococcal polysaccharide vaccine on nasopharyngeal colonisation following human infection challenge with serotype 3 and serotype 6B (PREVENTING PNEUMO 2): a double-masked, randomised, controlled, phase 4 trial.
Journal article
Liatsikos K. et al, (2026), Lancet Microbe, 7
Machine learning-driven identification of serotype-independent pneumococcal vaccine candidates using samples from human infection challenge studies
Preprint
Cheliotis KS. et al, (2025)
Machine Learning-Driven Identification of Serotype-Independent Pneumococcal Vaccine Candidates using samples from Human Infection Challenge Studies
Preprint
Cheliotis KS. et al, (2025)
High Respiratory Syncytial Virus Burden in Children Under 3 Years of Age Across All Care Levels in England
Preprint
Carter EC. et al, (2025)

