Prof. Dr. rer. nat. Fred Hamprecht

Interdisciplinary Center for Scientific Computing (IWR)
Heidelberg University



1993-1998 Undergraduate Studies in Chemistry
ETH Zürich, EPF Lausanne,
Imperial College London, Cambridge University
2001 Dr. rer. nat., ETH Zurich
2001 Postdoctoral Fellow
Seminar for Statistics, ETH Zurich
2001 – 2007 Associate (C3) Professor for Multidimensional Image Processing, Heidelberg
2007 – 2011 Affiliate Professor
Childrens’ Hospital, Boston
Since 2008 Full Professor for Image Analysis and Learning, Heidelberg University
Since 2011 Visiting Scientist
HHMI Janelia Research Campus
2014 – 2015 Weston Visiting Professor
Dept. of Applied Mathematics and Computer Science
Weizmann Institute for Science and Technology, Rehovot



1993 – 1998 Scholar of the German National Scholarship Foundation
2007 Price for IT & LifeScience: bwcon 2007 (jointly with B. H. Menze, B. M. Kelm, C. Zechmann)
2008 DAGM 2008 Award (jointly with B. Andres, U. Köthe, M. Helmstädter, W. Denk)
2012 Machine Learning in Medical Imaging MLMI 2012 best paper award (jointly with X. Lou, L. Fiaschi, U. Köthe)
2013 DAGM 2013 Award (jointly with C. Strähle, U. Köthe)
2014 MICCAI Brain Tumor Segmentation Challenge (BraTS 2014): first prize (with J. Kleesiek, G. Urban et al.)
2016 ISBI 2012, SNEMI3D and CREMI connectomics segmentation challenges: Top of leaderboard
2018 GCPR 2018 Award (jointly with T. Hehn)



2004 – 2010 Steering Committee of “Deutsche Arbeitsgemeinschaft für Mustererkennung (DAGM)
2006 – 2008 Coordinator , Technical Platform of “Viroquant” Systems Biology Collaborative Research Initiative
2007 – 2012 PI, “Zukunftskonzept” of Heidelberg University within the German Excellence Initiative
Since 2007 PI, Excellence Initiative Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences “HGS MathComp”
Since 2008 Co-founder and Director (jointly with B. Jähne, B. Ommer, C. Schnörr), Heidelberg Collaboratory for Image Processing (HCI)
2013 – 2015 Head, CellNetworks “MathClinic” image processing core facility
2015 Area Chair: CVPR 2015 (most highly cited venue in computer Vision)



Workflow zur automatisierten Erkennung von Anomalien mit wenig Labelaufwand. M. Kandemir, F. A. Hamprecht, U. Schmidt, C. Wojek, Patent application, number: DE 10 2015 114 015.2

Self Adjustment of Scanning Electron Microscopes / Selbstadaptivität von Rasterelektronenmikroskopen. M. Staudacher, F. A. Hamprecht, L. Görlitz
Patent, Patent Number: WO2009/062781 A1

Method for processing an intensity image of a microscope. M. Staudacher, F. A. Hamprecht, L. Görlitz
Patent, Patent Number: WO2008/034721-A1



Peter, S., Diego, F., Hamprecht, F. A., & Nadler, B. (2017). Cost efficient gradient boosting. In Advances in Neural Information Processing Systems (pp. 1551-1561).

Hamprecht, F. A., Achleitner, U., Krismer, A. C., Lindner, K. H., Wenzel, V., Strohmenger, H. U., … & Amann, A. (2001). Fibrillation power, an alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation. Resuscitation, 50(3), 287-296.

Menze, B. H., Lichy, M. P., Bachert, P., Kelm, B. M., Schlemmer, H. P., & Hamprecht, F. A. (2006). Optimal classification of long echo time in vivo magnetic resonance spectra in the detection of recurrent brain tumors. NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In vivo, 19(5), 599-609.

Kandemir, M., & Hamprecht, F. A. (2015). Computer-aided diagnosis from weak supervision: a benchmarking study. Computerized medical imaging and graphics, 42, 44-50.

Hanselmann, M., Kirchner, M., Renard, B. Y., Amstalden, E. R., Glunde, K., Heeren, R. M., & Hamprecht, F. A. (2008). Concise representation of mass spectrometry images by probabilistic latent semantic analysis. Analytical chemistry, 80(24), 9649-9658.