About

Robert Free is a Lecturer in Health Data Science at the University of Leicester and the Director of Informatics for the NIHR Leicester Biomedical Research Centre (BRC) who has worked at the clinical interface between healthcare and technology for many years, with expertise in clinical informatics, software engineering, applied artificial intelligence/machine learning (AI/ML), molecular biology/genetics and bioinformatics.
His research group focus on the use of advanced data science (including AI/ML) to develop and translate models and technologies into smart data-driven tools for improving healthcare outcomes. He is particularly interested in the use and integration of complex data from different disciplines for this purpose including ‘omics data, clinical data of different types (test results, coded observations, imaging) and mobile digital health data collection. Current projects being led by Dr Free, or to which he is contributing or has contributed include development of AI-based digital twins for respiratory emergency admissions, AI/ML-based models to predict community acquired pneumonia outcome from complex multi-faceted hospital admission data and generic approaches for embedding logical and AI/ML models into data-driven workflows to provide trusted/interpretable clinical decision support to healthcare workers.
Dr Free has supervised/supported informatics projects as technical lead and co-I within several high impact clinical studies and interdisciplinary initiatives, including the East Midland Breathomics Pathology Node, the Extended Cohort for E-health, Environment and DNA and nationally important pandemic related projects including the UK Research study into Ethnicity and COVID-19 outcomes in Healthcare workers.
As Leicester BRC’s Director of Informatics, he oversees the BRC’s Health Informatics Platform through which he is facilitating and develop exciting interdisciplinary research collaborations and partnerships in data science working with other BRCs and researchers locally, regionally and nationally.