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Langs Georg

Univ.-Prof. Dipl.-Ing. Dr. Georg Langs|© Adrian Dalca

Univ.-Prof. Dipl.-Ing. Dr. Georg Langs

Director

Contact

E-Mail: georg.langs@meduniwien.ac.at
Phone: +43 (0)1 40400-73725 
Assistant: Rosa Yesil +43 (0)1 40400-73926 

Medical University of Vienna
Department of Biomedical Imaging and Image-guided Therapy
Computational Imaging Research Lab
Waehringer Guertel 18-20
1090 Vienna, Austria

Office: Anna Spiegel Center of Translational Research (Building 25, Floor 7, Room 28)

I am also affiliated with the Medical Vision Group at CSAIL, Massachusetts Institute of Technology, where I work in the group of Polina Golland. http://people.csail.mit.edu/langs

Georg Langs studied Mathematics at Vienna University of Technology, and finished his PhD in Computer Vision at Vienna University of Technology and Graz University of Technology in 2007. He worked as a post-doctoral associate at the Applied Mathematics and Systems Laboratory at Ecole Centrale de Paris, and the GALEN Group at INRIA-Saclay, Ile de France with Nikos Paragios from 2007 to 2008. He was a Research Scientist at Computer Science and Artificial Intelligence Laboratory at Massachusetts Institute of Technology from 2009 to 2011, and joined the Faculty of Medical University of Vienna in 2011. He taught Computer Vision and Medical Imaging courses at Ecole Centrale de Paris, and teaches at Vienna University of Technology. He reviews for several Conferences and Journals, among them IEEE Transactions on Pattern Recogniton and Machine Intelligence, and IEEE Transactions on Medical Imaging. Georg Langs is the Head of the Computational Image Analysis and Radiology Lab (CIR) at the Medical University of Vienna.

Research interests

Neuroimaging, machine learning and medical image analysis,
in particular:

  • Machine learning in medical imaging
  • Computational Neuroscience
  • Bridging imaging phenotypes and biological mechanisms
  • Learning from large scale heterogeneous clinical data
  • Started WWTF funded project PREDICTOME to study the dynamics of breast cancer during neoadjuvant chemotherapy 
  • Started FWF funded project ONSET to develop machine learning methods for the early detection of future pandemics and the rapid creation of prediction models from early observational data during a pandemic.  

All publications are here