Carola Heinzel

Currently, I am a PhD student in the probability group within the mathematical institute of the University of Freiburg.

I am a member of the CRC Small Data.

Address:

Abteilung für Mathematische Stochastik
Albert-Ludwigs University of Freiburg
Ernst-Zermelo-Straße 1

Room 231
D - 79104 Freiburg

E-Mail: carola.heinzel@stochastik.uni-freiburg.de

Carola Heinzel

Research topics and interests

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

Publications

My ORCID profile is here.

Heinzel, C. A Statistical Test for Comparing the Linkage and Admixture Model Based on Central Limit Theorems. submitted. 2025.
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., 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(9), 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.