Vincent Wieland
2020 - B.Sc. Mathematics, University of Bonn
2022 - B.Sc Economics, University of Bonn
2023 - M.Sc Mathematics, University of Bonn
Since April 2023 - PhD Candidate in Mathematics and Life Science, University of Bonn
Currently working on stochastic modelling of disease progression and Bayesian inference clinical trajectory analysis.
Contact: vincent.wieland@uni-bonn.de
Sessions
This project addresses a critical challenge in clinical data analysis, particularly in oncology. We propose a mathematical model for cancer patients' disease progression, merging stochastic dynamics from various data modalities. Utilizing Bayesian inference, we illustrate this with a simulated study on tumor growth, metastases, and patient survival. Leveraging Julia, our approach provides estimation of combined stochastic models, paving the way for comprehensive clinical trajectory analysis.
This project leverages the Julia programming language to construct a robust mechanistic model for understanding infectious disease transmission and reporting. Integrating diverse data sources, i.e. officially reported case counts and wastewater measurements, we address the inherent limitations of delayed reports, underascertainment and high stochasticity of observations. The efficiency and modularity of Julia empower us to tackle this complex modeling and estimation task effectively.