Biography
Alexia’s post doctoral work at the CEU mainly focuses on longer-term effects of Covid-19 using whole population electronic health records within the CVD-COVID-UK consortium. Alexia’s goal is to pursue a career in researching concepts by aggregating environmental and health data, developing AI technologies, applying machine learning algorithms and learning more about epidemiology, population health data, missing data, and prediction modelling. Alexia holds a BEng and MEng in Environmental Engineering by Democritus University of Thrace. During her undergraduate studies she was part of a research team where she focused on Big Data analysis, statistical modelling, infodemiology and Internet behaviour. Then she moved to Scotland and completed a MSc in Big Data with distinction, at the University of Stirling. For her dissertation, she applied unsupervised learning techniques to predict water quality parameters using remote sensing data. Whilst in Stirling, she decided to undertake the exciting opportunity to join the Centre for Health Informatics in the University of Manchester. She started her PhD on Health Informatics which was supervised by Prof Peek, Prof Geifman and Dr Couch, and funded by EPSRC. Her research focused on probabilistic methods to integrate structured biomedical data. During her PhD, she co-authored research papers, was management committee member in different European Networks, participated in training schools, completed Short Term Scientific Missions and presented her research on multiple international and national meetings, symposia and conferences. She was also involved in teaching of many UG and PG courses which led her to obtain a Fellowship by Advance HE.
Research
Dr Alexia Sampri is a Research Associate in Health Data Science at the University of Cambridge, where she leverages her expertise in statistical analysis and machine learning to explore the long-term effects of Covid-19 on cardiovascular and inflammatory diseases using electronic health records. With a focus on data integration and public health, her work aims to help patient outcomes through innovative epidemiological approaches and bioinformatics. Dr Sampri is also actively involved in public engagement, hosting the podcast Health Data Science Insights – Cambridge, which discusses advancements in population health and multi-omics approaches, while emphasizing the importance of understanding the impact of environmental exposures on health.
Publications
1. Kerr S, Bedston S, Cezard G, Sampri A, et al. (2024). "Under-vaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies of over 64 million people in England, Northern Ireland, Scotland, and Wales." The Lancet. 2024;403(10426):554-566. doi:10.1016/S0140-6736(23)02467-4.
2. Sampri, Alexia (2022) 'Probabilistic Approaches for Data Integration in Biomedical Research', PhD thesis, The University of Manchester, Manchester, UK
3. Marcos-Zambrano LJ, et al. (2023). "A toolbox of machine learning software to support microbiome analysis." Frontiers in Microbiology, 14: 1250806. doi: 10.3389/fmicb.2023.1250806.
4. D'Elia D, et al. (2023). "Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action." Frontiers in Microbiology, 14: 1257002. doi: 10.3389/fmicb.2023.1257002.
5. Peters S, Vienneau D, Sampri A, Turner M, Castaño Vinyals G, Bugge M, Vermeulen R. (2021) "Occupational exposure assessment tools in Europe: a comprehensive inventory overview." Annals of Work Exposures and Health, 66(5): 671-686.
6. Moreno-Indias I, et al. (2021) "Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions." Frontiers in Microbiology, 12: 277.
7. Sampri A, Geifman N, Le Sueur H, Doherty P, Couch P, Bruce I, Peek N, MASTERplans Consortium. (2020) "Probabilistic Approaches to Overcome Content Heterogeneity in Data Integration: A Study Case in Systematic Lupus Erythematosus." Studies in Health Technology and Informatics, 270: 387-391.
8. Mavragani A, Sampri A, Sypsa K, Tsagarakis KP. (2018) "Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era." JMIR Public Health and Surveillance, 4(1): e24.
9. Sampri A, Mavragani A, Tsagarakis KP. (2016) "Evaluating Google Trends as a tool for integrating the ‘Smart Health’ concept in the Smart Cities' governance in USA." Procedia Engineering, 162: 585-592.
10. Mavragani A, Sypsa K, Sampri A, Tsagarakis KP. (2016) "Quantifying the UK Online Interest in substances of the EU Watch List for Water Monitoring: Diclofenac, Estradiol, and the Macrolide Antibiotics." Water, 8(11): 542.
Other Professional Activities
Leading the ‘Health Data Science Insights – Cambridge’ Podcast https://open.spotify.com/show/5C8UU5yoGqIPOlgULAeHTQ?si=fbd9800d8b124bd5 Management committee member: Web-centred linguistic data science| ‘Statistical and machine learning techniques in human microbiome studies| Personalised medicine in chronic kidney disease: improved outcome based on Big Data Working Member: Network for implementing multi-omics approaches in atherosclerotic cardiovascular disease prevention and research| European Burden of Disease Network| International Interdisciplinary Network on Smart Healthy Age-friendly Environments | Global Digital Human Rights Network
