Niko Beerenwinkel
Niko Beerenwinkel connects mathematics, statistics and computer science with biology and medicine. Beerenwinkel earned a computer-science doctorate at Saarland in 2004, worked as a postdoctoral researcher at Berkeley and Harvard, and joined ETH in 2007. His work includes probabilistic models, genomic data analysis and methods for understanding the genetic diversity of tumors and pathogens. A 2020 ETH report describes his group’s machine-learning methods for identifying meaningful tumor variation in noisy genomic measurements. As of October 2026, Beerenwinkel works on computational methods for tumor evolution and viral genomic diversity. These are research tools that support biomedical analysis.
- Now at
- ETH Zurich
- Works
- 567
- Citations
- 22,357
- h-index
- 68
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2004–2007
Doctoral and postdoctoral research
Beerenwinkel earned a computer-science doctorate at Saarland in 2004, followed by postdoctoral work at Berkeley and Harvard before joining ETH in 2007. He had previously trained in mathematics and biology at Bonn.
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Spring 2016
Computational genomics programme
Beerenwinkel was a visiting scientist in Algorithmic Challenges in Genomics in spring 2016. His research includes methods for virus populations, HIV drug resistance and probabilistic network reconstruction.
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2020
Learning from noisy tumor data
His group develops machine-learning methods for finding and interpreting genetic diversity in tumors. It explains the need to separate noise from useful genomic signals.
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As of October 2026
Tumor evolution and viral diversity
His lab develops methods for reconstructing tumor evolution, analyzing single-cell genomic data and estimating viral genetic diversity. He is a professor of computational biology.
Sources and credits
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