Mozhdeh Shiranirad

Mozhdeh Shiranirad is a Research Fellow in Machine Learning at the University of Southampton's School of Mathematical Sciences. Her work focuses on applying AI and mathematical modeling to investigate early-onset burdensome multimorbidity, leveraging data from birth cohorts and healthcare records. She holds a PhD in chemical engineering, with prior roles in industrial research and academic research in machine learning applications.

• Education: PhD in Chemical Engineering (focus on machine learning for material simulations).
• Research Groups: Applied Mathematics and Theoretical Physics, Mathematical Modelling.

Her research interests include AI-driven healthcare solutions, data science methodologies, and programming development for health-related challenges. Recent work emphasizes early-life determinants of multimorbidity and the development of predictive models for public health interventions. Collaborations span interdisciplinary teams addressing healthcare data integration and outcomes analysis.

Publications (2023–2025) highlight trends in leveraging cohort studies, electronic health records, and machine learning to dissect multimorbidity burdens and inform preventative strategies.

Awards/Grants: No awards explicitly listed in the provided text.

Advising: Currently no listed PhD/Master’s students. Research contributions include collaborative projects with institutions like the SAIL Databank and NHS datasets.

Labs/Teams: Active in the MELD-B collaborative initiative, focusing on interdisciplinary healthcare research.