معرفی
Luna De Ferrari is a Senior Research Officer (GAIL) at the School of Informatics, University of Edinburgh. She leads research support activities in the Generative AI Lab, focusing on optimizing GPU resource allocation via Kubernetes and supporting AI workflows. Previously, she served as AI coordinator for the NIHR-funded AIM-CISC project (2021-2024) exploring multimorbidity patterns. Her career includes roles as a data scientist at the Edinburgh Parallel Computing Centre, statistics/R programming coordinator in Psychology, and researcher in epigenome-wide DNA methylation studies at the Institute for Genomic and Molecular Medicine. Her technical expertise spans machine learning, NLP, Python/R programming, and distributed systems (Docker/Kubernetes).
Education:
- PhD in Philosophy, University of Edinburgh (2012)
- MSc in Informatics, University of Edinburgh (2005)
- BSc in Biomedical Science (Industrial Biotechnology), Università degli Studi di Milano Bicocca (2000)
Research Interests:
Her work bridges computational methods and biomedical applications, focusing on:
- Machine Learning: predictive modeling for enzyme mechanisms, epigenetic patterns, and clinical outcomes
- Health Informatics: clustering analysis of chronic conditions, multimorbidity patterns, and healthcare data
- Bioinformatics: enzyme function prediction, molecular curation systems, and genomic data analysis
Key Contributions:
Her recent work includes developing clustering algorithms for 7.5 million patient records to better understand multimorbidity patterns, and umbrella reviews evaluating holistic interventions for frailty management. Earlier research pioneered machine learning approaches for enzyme mechanism prediction using InterPro signatures (2012-2015), and contributed to epigenetic studies of bone diseases (2015).
Technical Expertise:
- Advanced proficiency in ML frameworks, NLP, and LLM-supported coding
- Strong systems engineering background with Kubernetes/Docker
- Experience managing large-scale biomedical datasets and collaborative curation projects
