Bjoern H. Menze

Also known as Björn Menze

Bjoern H. Menze is a researcher in biomedical image analysis and machine learning whose work applies computational modeling to clinical neuroimaging and oncology. He earned physics master's degrees at Uppsala University in 2002 and Heidelberg University in 2004, completed a computer science PhD at Heidelberg in 2007, and did postdoctoral research at Harvard Medical School and MIT's CSAIL. After working at ETH Zurich from 2011 to 2013, he joined the Technical University of Munich in 2013, coauthored vascular network work at MICCAI 2014 and the 2015 BRATS benchmark report, and became a W3 professor at TUM and TranslaTUM in 2019. Since September 2020, he is a full professor at the University of Zurich, and in 2026 he serves as deputy director of its Children & Cancer National Center of Competence in Research.

Now at: University of Zurich

Timeline

2002–2007

Physics degrees and a Heidelberg PhD

He earns physics master's degrees from Uppsala University in 2002 and Heidelberg University in 2004. In 2007, he completes a computer science PhD at Heidelberg's Interdisciplinary Center for Scientific Computing, working with Fred Hamprecht.
2009–2011

Medical vision in Boston

Before his 2013 TUM appointment, he works as a postdoc in Boston at Harvard Medical School's BWH Surgical Planning Lab with Ron Kikinis and, from 2009 to 2011, in MIT's CSAIL Medical Vision group with Polina Golland.
2011–2013

Professor at TUM

From 2011 to 2013, he works as a senior researcher and lecturer in ETH Zurich's Computer Vision Laboratory before joining TUM in 2013 as its first Rudolf Mößbauer Tenure Track Professor. At TUM's Munich School of Bioengineering, his group works on medical computer vision, image-based modeling, and computational physiology, with an oncology focus.
2014

Vascular network extraction

At MICCAI 2014, he coauthors “Extracting vascular networks under physiological constraints via integer programming,” which wins the Medical Image Analysis Award for the best paper of MICCAI 2014 and appears in Medical Image Analysis's 2014 Best Paper Issue.
2015

Reporting the BraTS benchmark

In 2015, he and coauthors report the setup and results of the Multimodal Brain Tumor Image Segmentation Benchmark, which they organize with MICCAI in 2012 and 2013. At MICCAI 2015, he receives the Young Scientist Publication Impact Award.
2019

W3 professorship at TranslaTUM

In 2019, he is appointed W3 Professor for Image-Based Biomedical Modelling at the Munich School of BioEngineering and the Zentralinstitut fuer translationale Krebsforschung (TranslaTUM).
Since September 2020

Professor at the University of Zurich

Since September 2020, he is a full professor of Biomedical Image Analysis and Machine Learning in the Department of Quantitative Biomedicine at UZH, funded by the Helmut Horten Foundation. His work uses machine learning, biophysics, and computational physiology for biomedical image computing, clinical neuroimaging, and tumor growth modeling.
2026

Deputy director at Children & Cancer

In 2026, he serves as Deputy Director of the Children & Cancer National Center of Competence in Research at the University of Zurich.

Career

Since 2026University of ZurichFull Professor of Biomedical Image Analysis and Machine Learning
From 2013Technical University of MunichRudolf Mößbauer Tenure Track Professor
MIT CSAILPostdoctoral Researcher
Mass General BrighamPostdoctoral Researcher
ETH ZurichSenior Researcher and Lecturer