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Fellow-Klasse 2010/11Prof. Dr. Fred Hamprecht

Arbeitsvorhaben am Marsilius-Kolleg

Networks: quantitative analysis in real-world settings

Some of the most interesting and relevant social, scientific and economic phenomena can most aptly be described in terms of networks. While many of these networks are not new in themselves, they now become observable for the first time due to a data accumulation that is without historical precedent. These new data allow and inspire new questions that in turn call for new automated and quantitative analysis techniques.

The aim of this project is to develop new algorithms that exploit network structure to solve exemplary concrete problems in the neurosciences and socioeconomic geography; and to work with the other Fellows to identify and discuss the possible impact of network analysis in their respective fields.


Details of exemplary problems and desired cooperations are given in the following:


Network Analysis in the Neurosciences * 


My group is working in image analysis and is taking part in a worldwide race for the reconstruction of the "connectome" (wiring diagram) of the human brain. The reconstruction itself exploits ideas from graphical models, and is hence based on networks; but even once a satisfactory reconstruction is obtained, a characterization and analysis of the network of billions of neurons at a higher level of abstraction will be necessary to make advances towards an understanding of neural computation and, ultimately, cognition. 

Data of this kind is currently acquired at the MPI in Heidelberg (W Denk). Recent developments by local microscopists and biologists (J Wittbrodt, E Stelzer, S Ryu) raise hopes to track the evolution of an entire neural system in statu nascendi. Such evolving networks are of great interest to Marsilius fellow G Reinelt.


Empirical social networks *

The partial shift of human communication to computer-based resources (VoIP, messaging services, email, social websites, blogs, . . . ) is now generating traces that are amenable to fully automated analysis. Current work [Leskovec 2008] exploits billions of messages between millions of users to establish patterns of human (digital) communication. Smaller networks attributed with more expressive features are currently established by Marsilius fellow J Glueckler. 

I am also looking forward to discuss with the other Fellows possible implications for their fields. Specifically, if there is interest from colleagues in law and ethics, I would like to organize a joint seminar for students from computer science & physics, law and philosophy to discuss the opportunities and possible abuses of (wireless) sensor and surveillance networks.

Porträt Fred Hamprecht Fellow 2010/11



  • 01/08 Co-founder and Director, Heidelberg Collaboratory for Image Processing (HCI)
  • 11/07-present PI, "Zukunftskonzept" of Heidelberg Univ. within the German Excellence Initiative
  • 11/07-present  PI, Heidelberg Grad. School of Math. and Comp. Methods for the Sciences
  • 01/07-present Scientific consulting for Heidelberger Druckmaschinen AG
  • 12/06-04/08 Coordinator, Technical Platform of "Viroquant" Research Initiative
  • 11/06-present Investigator, Excellence Cluster on "Cellular Networks" at Heidelberg Univ.
  • 07/06-present Affiliated Professor in the Pathology Department, Children's Hospital, Boston
  • 10/01-present Scientific consulting for Robert Bosch GmbH
  • 10/01-present Professor for Multidimensional Image Processing, University of Heidelberg
  • 04/01-08/01 Post-doc, Seminar for Statistics, ETH Zurich
  • 07/98-02/01 Graduate studies, ETH Zurich
  • 10/93-03/98 Studies of Chemistry at ETH Zurich, EPF Lausanne, Imperial College London, University of Cambridge

Ausgewählte Publikationen


B. Andres, U. Köthe, M. Helmstaedter, W. Denk, F. A. Hamprecht: Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification. DAGM 2008: 142-152.
H. R. Künsch, E. Agrell, F. A. Hamprecht: Optimal lattices for sampling. IEEE Transactions on Information Theory 51(2): 634-647 (2005).
B. Y. Renard, M. Kirchner, H. Steen, J.A.J. Steen, F. A. Hamprecht: NITPICK, peak identifcation for mass spectrometry data. BMC Bioinformatics 2008, 9:355.
F. A. Hamprecht, W. Thiel, W. F. van Gunsteren: Chemical Library Subset Selection Algorithms: A Unied Derivation Using Spatial Statistics. Journal of Chemical Information and Computer Sciences 42(2): 414-428 (2002).
J. Steen, H. Steen, A. Georgi, K. Parker, M. Springer, M. Kirchner, F. A. Hamprecht, M. W. Kirschner: Different Phosphorylation States of the Anaphase Promoting Complex in Response to Anti-Mitotic Drugs: A Quantitative Proteomic Analysis. Proceedings of the National Academy of Sciences, (2008) 105,16, 6069-6074.
B. M. Kelm, B. H. Menze, C. M. Zechmann, K. T. Baudendistel, F. A. Hamprecht: Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification. Magnetic Resonance in Medicine, (2007) 57, 150-159.
F. A. Hamprecht, A. J. Cohen, D. J. Tozer, N. C. Handy: Development and assessment of new exchange-correlation functionals. Journal of Chemical Physics, (1998) 109, 6264-6271.
M. Jager, C. Knoll, F. A. Hamprecht: Weakly Supervised Learning of a Classifier for Unusual Event Detection. IEEE Transactions on Image Processing 17(9): 1700-1708 (2008).
Towards Digital Staining using Imaging Mass Spectrometry and Random Forests M. Hanselmann, U. Köthe, M. Kirchner, B. Y. Renard, E. R. Amstalden, K. Glunde, R. M. A. Heeren, F. A. Hamprecht Journal of Proteome Research, (2009) 8, 3558-3567.
F. A. Hamprecht, U. Achleitner, A. C. Krismer, K. H. Lindner, V. Wenzel, H.-U. Strohmenger, W. Thiel, W. F. van Gunsteren: Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular -brillation. Resuscitation, (2001) 50, 287-296.


Prof. Dr. fred hamprecht

Heidelberg Collaboratory for Image Processing 
Ruprecht-Karls-Universität Heidelberg
E-Mail: fred.hamprecht@iwr.uni-heidelberg.de