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Institute News

Guest Editor

  • 24 January 2014

Peer Fischer is guest editor for the Nanoscale themed issue on “Helical Micro- and Nanostructures” (Nanoscale, 2014).

Peer Fischer

Good luck

  • 15 January 2014

Our lab's recent graduate Dr. Eric Diller will be an assistant professor at the University of Toronto (Mechanical and Industrial Engineering Department) from January 2014.

Metin Sitti

The geometry of cancer cells

  • 05 December 2013

Malignant and healthy cells display characteristic fractal patterns, which can be used to tell them apart

new approach has given rise to the hope for a faster and more reliable method for determining cancer cell types. Scientists from the Max Planck Institute for Intelligent Systems in Stuttgart and the University of Heidelberg found that cells can be very accurately characterised using fractal geometry. This theory describes objects whose minute structural details resemble their larger contours. Cancer cells are not able to regulate their growth and, as a consequence their shape, as effectively as healthy cells. The particular fractal geometry of a cell therefore becomes a marker of the cell type. Using this mathematical method in combination with sophisticated image recognition, it is possible to establish the progression of cancer in a cell. The researchers studied the statistical distribution of the occurrence of structural details on the surface of different tumour cells, and were thus able to identify cancer cells with more accuracy than when using the conventional immunohistological method. Moreover, they were able to distinguish between different tumours.

Michael Black awarded 2013 Helmholtz Prize

  • 01 December 2013

2013 Helmholtz Prize honors Michael J. Black's work on robust optical flow estimation described in the ICCV 1993 paper with P. Anandan on "A framework for the robust estimation of optical flow."

Michael Black

NIPS 2013 outstanding paper award

  • 01 December 2013

Manuel Gomez-Rodriguez, Department Empirical Inference (Prof. Schölkopf), received an outstanding paper award at NIPS 2013.

Manuel Gomez Rodriguez

Cover Article

  • 18 November 2013

Our paper on “Plasmonic nanohelix metamaterials with tailorable giant circular dichroism” is the featured cover article for the Applied Physics Letters Issue 21, vol. 103, 18 November 2013.

John Gibbs Andrew Mark Sahand Eslami Peer Fischer

National Science Foundation

  • 02 November 2013

Our lab alumnus Prof. Seok Kim at UIUC will receive the prestigious National Science Foundation (NSF) CAREER Award for his research and educational activities on microassembly using transfer printing.

Metin Sitti

Stefan Schaal elected IEEE Fellow 2014

  • 01 November 2013

For his contributions to robot learning and modular motion planning.

Stefan Schaal

2013 Young Investigator Award der International Neural Networks Society für Prof. Jan Peters

  • 29 October 2013

Preis für entscheidende Beiträge im Bereich der Neuronalen Netzwerke

Tübingen. Prof. Ph.D. Jan Peters, Leiter des „Robot-Learning-Labs“ am MPI für Intelligente Systeme, ist mit dem 2013 Young Investigator Award der International Neural Network Society ausgezeichnet worden. Peters hat den Preis erhalten für seine entscheidenden Beiträge im Bereich der Neuronalen Netzwerke, insbesondere zur Entwicklung neuer Lernmethoden, die es Robotern erlauben, neue Fähigkeiten zur Bewegung zu lernen.

Jan Peters

Summer School "Maschinelles Lernen für Personalisierte Medizin"

  • 23 September 2013

An der Schnittstelle zwischen Maschinellem Lernen und Statistischer Genetik

Tübingen. Vom 23. Bis 27. September 2013 besuchen rund 70 Teilnehmerinnen und Teilnehmer die „Machine Learning for Personalized Medicine“ (MLPM) Summer School am Max-Planck-Campus Tübingen. Maschinelles Lernen entwickelt sich zur Schlüsseldisziplin zur Bewältigung riesiger Datenmengen – unter anderem in der Biologie und Medizin. Bisher mangelt es aber an Fachkräften in diesem Bereich. Das EU-geförderte und von Prof. Dr. Karsten Borgwardt koordinierte MLPM-Projekt bildet in den kommenden drei Jahren international 14 Nachwuchswissenschaftler an der Schnittstelle von Maschinellem Lernen und Statistischer Genetik aus. Sie sollen künftig dazu beitragen, entscheidende Hindernisse für die personalisierte Medizin zu bewältigen.

Karsten Borgwardt Matthias Tröndle