Gonca Buyrukoglu received her B.S. degree in Statistics from Anadolu University, Eskişehir, in 2010, her M.Sc. in Statistics (Biostatistics Pathway) from the University of Manchester, UK, in 2014, and her Ph.D. in Statistics from Northumbria University, Newcastle, in 2019. Her doctoral research focused on developing methodologies for multilevel and multivariate joint models to address complex longitudinal data. The methodology is tested via simulation studies and applied to real datasets such as the Scleroderma Lung Study, a liver cirrhosis trial, and the ADNI project. She later extended her research to survival analysis in breast cancer and the dynamic prediction of excessive daytime sleepiness in Parkinson’s disease. In August 2025, she joined the Department of Molecular Biology and Genetics at Abdullah Gül University, where she continues to advance statistical methodologies with applications in cancer research. Her main research interests include joint modelling of longitudinal and survival data, statistical modelling in cancer research, time-to-event analysis, ensemble learning, and the application of machine learning methods in the life sciences.