Nuala J. Meyer

The paper identifies persistently activated virus-specific CD8 T cells in long COVID patients, suggesting chronic antigen stimulation by SARS-CoV-2 or herpesvirus.

The paper develops MAESTRO, a self-supervised deep learning framework to transform immune profiles into embeddings capturing immune health, enabling clinical prediction and precision immunotherapy.

The paper identifies a novel framework to quantify immune dysregulation in critical illness by analyzing transcriptomic data across multiple cohorts.

This paper introduces UNITO, a deep learning framework for automated cytometric gating that matches human performance and provides interpretable results without requiring manual input.

The paper introduces cyMAE, a masked autoencoder for automated immunophenotyping, showing it improves accuracy and interpretability over manual methods in cytometry data analysis.

This paper conducts a genome-wide association study (GWAS) to identify genetic variants associated with 28-day survival in sepsis patients, finding three novel variants linked to reduced survival.