Dr. Dominic Edelmann

Research Topics                  

• Distance correlation
• Survival analysis for high-dimensional molecular data
• Innovative clinical trials
• Machine learning
• Epigenetic data

Education/Degrees 

Dr. rer. nat., Mathematics, Heidelberg University, 2011-2015

Diplom, Mathematics, Heidelberg University, 2004-2011

Previous appointments

Research Assistant, Heidelberg University, 2011-2015   

Selected publications

• Edelmann, D., Goeman, J. (2021). A Regression Perspective on Generalized Distance Covariance and the Hilbert-Schmidt Independence Criterion. Statistical Science. Accepted for publication.
• Edelmann, D., Welchowski, T., and Benner, A. (2021). A consistent version of distance covariance for right‐censored survival data and its application in hypothesis testing. Biometrics. Accepted for publication.
• Edelmann, D., Saadati, M., Putter, H., and Goeman, J. (2021). A global test for competing risks survival analysis. Statistical Methods in Medical Research. Accepted for publication.
• Edelmann, D., Móri, T. F., and Székely, G. J. (2021). On relationships between the Pearson and the Distance Correlation Coefficients. Statistics and Probability Letters 169.
• Edelmann, D., Vogel, D., and Richards, D. (2020). The distance standard deviation. Annals of Statistics 48, 3395-3416.
• Gündert, M., Edelmann, D., Benner, A., Jansen, L., Jia, M., Walter, V., Knebel, P., Herpel, E., Chang-Claude, J., Hoffmeister, M., Brenner, H. and Burwinkel, B. (2019). Genome-wide DNA methylation analysis reveals a prognostic classifier for non-metastatic colorectal cancer (ProMCol classifier). Gut 68, 101-110.
• Edelmann, D., Fokianos, K., and Pitsillou, M. (2019). An updated literature review of distance correlation and its applications to time series. International Statistical Review 87, 237-262.
• Dueck, J., Edelmann, D., Gneiting, T. and Richards, D. (2014). The affinely invariant distance correlation. Bernoulli 20, 2305-2330.

Supervision

Roman Nagurski (Master’s thesis, co-supervisor with Jan Johannes): A Bias-corrected Estimator for Distance Correlation and its Application in Biostatistics

Agnes Gambietz (Master’s thesis, co-supervisor with Jan Johannes): Regression Models for Bounded Responses with Application to DNA Methylation

Funding

DFG Grant „dCortools: Distanzkorrelationsverfahren zur Erkennung Nichtlinearer Zusammenhänge in Hochdimensionalen Molekularen Daten“, 2019 –

Other

Newspaper article: https://www.sueddeutsche.de/karriere/arbeit-mathematiker-sind-multitalente-dpa.urn-newsml-dpa-com-20090101-170707-99-155123