Dominic Edelmann

Dominic Edelmann is a researcher at Heidelberg University, Germany, specializing in mathematical statistics and its applications in biostatistics and high-dimensional molecular data. His work bridges theoretical statistics and biomedical research, particularly in developing and applying distance-based dependence measures.

Research Interests: His research centers on distance correlation, survival analysis for high-dimensional data, epigenetic data analysis, and machine learning. He investigates nonlinear relationships in complex datasets, with applications in oncology and molecular biology.

The recent publications show a strong trend in extending distance correlation methods to survival and competing risks data, as well as time series and high-dimensional settings. His work combines rigorous mathematical foundations with practical applications in biomedicine.

Scientific Funding:

• DFG Grant "dCortools: Distanzkorrelationsverfahren zur Erkennung Nichtlinearer Zusammenhänge in Hochdimensionalen Molekularen Daten" (2019–present)

Academic Supervision: He has co-supervised Master’s theses on bias correction in distance correlation and regression models for bounded responses in DNA methylation studies, indicating active involvement in training the next generation of statisticians.

He holds a Dr. rer. nat. in Mathematics from Heidelberg University (2015) and was a research assistant there during his doctoral studies. His work continues to be centered at Heidelberg University, contributing to both theoretical and applied statistical science.