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Dr. Dominic Edelmann

Dr. Dominic Edelmann

Dr. Dominic Edelmann




+49 6221 42 2393


TP 4



Research Topics                  

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



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.



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



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



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