Carola Heinzel

I am generally interested in probability theory and mathematical statistics, especially in their applications to the life sciences. I have worked on:

• Branching processes and their application to cancer research
• Linkage models
• Maximum entropy and its application to metabolic networks
• Machine learning and mathematics in forensic genetics

My ORCID profile is here.

• Dette, H., Heinzel, C., Lange, Z., Pfaffelhuber, P. Testing for Single-Population Ancestry in the Admixture Model. submitted. 2026.
• Farhadizadeh, M., Heinzel, C., Sigle, A., Binder, H., Wenz, F., Hasenauer, J., Pfaffelhuber, P., Binder, N. Typical Healthcare Pathways as a Basis for Admixture Modeling of Patient Trajectories. submitted. 2026.
• Heinzel, C., Pfaffelhuber, P., Wakolbinger, A. A small noise approximation for Muller's Ratchet. submitted. 2026.
• Schmitz, J., Naue, J., Hoffmann, L., Lange, Z., Suchanek, F., Lutz-Bonengel, S., Dette, H., Pfaffelhuber, P., Heinzel, C. In which cases does it make sense to classify an individual into one population and what are the alternatives? submitted. 2026.
• Maurer, T., Purucker, L., Hutter, F., Pfaffelhuber, P., Heinzel, C. Enhancing Intra-Continental Biogeographical Ancestry Prediction Through a Machine Learning Marker Selection Method. submitted. 2025.
• Heinzel, C. Statistical test to compare the linkage model and the admixture model based on central limit results. 171, 29-41, Theoretical Population Biology. 2026.
• Heinzel, C., Schweinsberg, J. Estimating the Growth Rate of a Birth and Death Process Using Data From a Small Sample. 88(5), Bulletin of Mathematical Biology. 2026.
• Heinzel, C. Consistency and central limit results for the maximum likelihood estimator in the Admixture Model. 166, 70-79, Theoretical Population Biology. 2025.
• Heinzel, C., Baumdicker, F., Pfaffelhuber, P. Revealing the range of equally likely estimates in the admixture model. 15(8), G3. 2025.
• Heinzel, C., Jadebeck, J., Zelle, E., Seiffarth, J., Nöh, K. Combining Knowledge About Metabolic Networks and Single-Cell Data with Maximum Entropy. 12(1), 3, Physical Sciences Forum. 2025.
• Heinzel, C., Purucker, L., Hutter, F., Pfaffelhuber, P. Advancing Biogeographical Ancestry Predictions Through Machine Learning. 79(103290), Forensic Science International: Genetics. 2025.

Winter Term 2026
Teaching Assistant for Measure Theory

Summer Term 2025
Teaching Assistant for Stochastic Analysis
Lecturer in Practical Exercises in Machine Learning

Winter Term 2023
Teaching Assistant for One-Dimensional Diffusions and Stochastic Differential Equations