Charis Damianidis
Biostatistician | Evidence Synthesis | Health Data Analytics
Hello, my name is Charis Damianidis. I am a PhD Student in Statistical Models in Meta-Analysis at the University of Ioannina and a Research Associate in the Evidence Synthesis Methods Team. My research interests focus on statistical methods for evidence synthesis, with particular emphasis on individual participant data meta-analysis, causal inference, treatment-effect heterogeneity, and health data analytics. I am open to discussing new ideas and potential collaborations related to these topics. Please feel free to contact me via email or connect with me on LinkedIn.
Announcements
March 2026
Started building my personal academic website.
Upcoming
More research updates, projects, and academic news will be posted here.
Projects
Master’s Thesis – Development of a Shiny Tool for Living Network Meta-Analysis
My master’s thesis, completed in the MSc program in Health Statistics and Data Analytics at the School of Medicine, Aristotle University of Thessaloniki, focuses on the development of an R Shiny application for Living Network Meta-Analysis, with a demonstration in chronic lymphocytic leukemia (CLL). The tool supports standard NMA and Component NMA workflows, including node merging, data exploration, model fitting, diagnostic assessment, visualization of key outputs, and export of structured HTML reports.
View project on GitHubAcademic Teaching Experience
Laboratory Instructor – Medical Statistics
Aristotle University of Thessaloniki | October 2025 – February 2026
Served as Laboratory Instructor for the Medical Statistics course for undergraduate medical students at the Aristotle University of Thessaloniki. I was responsible for delivering the practical component of the course, guiding students in the use of Jamovi for data management, descriptive statistics, and interpretation of statistical results. The laboratory sessions covered core biostatistical methods, including t-tests, ANOVA, and analyses of categorical data, with emphasis on the practical application of statistical concepts to real medical datasets. I also designed and delivered exercises aligned with the theoretical material of the course, supporting students in developing both methodological understanding and confidence in statistical reasoning.