Dr. Dominic Edelmann

Dr. Dominic Edelmann

Dr. Dominic Edelmann

Position:

Scientist

Phone:

+49 6221 42 2393

Fax:

+49 6221 42 2397

Building:

TP 4

Room:

S4.221

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., 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.*, Ohneberg, K.*, Becker, N., Benner A.*, and Schumacher, M.* (2020). Which patients to sample in clinical cohort studies when the number of events is high and measurement of additional markers is constrained by limited resources. Cancer Medicine 9, 7398-7406. (*: equal contribution)
  • Edelmann, D., Vogel, D., and Richards, D. (2020). The distance standard deviation. Annals of Statistics 48, 3395-3416.
  • Edelmann, D., Hummel, M., Hielscher, T., Saadati, M., and Benner, A. (2020). Marginal variable screening for survival endpoints. Biometrical Journal 62, 610-626.
  • Edelmann, D., Habermehl, C., Schlenk, R. F., and Benner, A. (2020). Adjusting Simon's optimal two-stage design for heterogeneous populations using historical controls. Biometrical Journal 62, 311-329.
  • 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.

 

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.morgenpost.de/wirtschaft/karriere/article211271459/Mathematiker-sind-Multitalente.html

 

 

 

 

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