Research Statement

Current Position
Research Scientist, Max Planck Institute for Biological Cybernetics, Tübingen
Dept.: Empirical Inference and Machine Learning (Bernhard Schölkopf)

Educational Background
2007-10Ph.D.
 supervised by Prof. David J.C. MacKay
 Cavendish Laboratory, University of Cambridge, UK
 Thesis Title: Approximate Inference in Graphical Models
2006-07Diplom Thesis
 supervised by Prof. Winfried Denk
 Max Planck Institute for Medical Research, Heidelberg, Germany
 Thesis Title: Point Spread Functions for Backscattered Imaging in the Scanning Electron Microscope
2004-05Exchange year
 Imperial College, London.
 Participation in the M.Sc. course "Quantum Fields and Fundamental Forces (passed all necessary examinations with a GPA of 75%, but exchange students can not be awarded degrees).
2001-07Diplom degree in Physics
 University of Heidelberg, Germany
 
Work Experience
2009/10Microsoft Research, Cambridge
 Freelance Consultant
2008Microsoft Research, Cambridge
 Internship
2007McKinsey & Company
 Summer Associate
 
Awards and Honors
2007-10Microsoft Research PhD Scholarship
2007Honorary Scholar of the Cambridge European Society
2005Lindau Nobel Meetings - Travel Stipend
 
Reviewing
2011Knowledge Discovery and Data Mining (Springer Journal)
 The Snowbird Conference
2010International Conference on Machine Learning
2009International Conference on Learning Theory
 
References, etc.
References are available upon request.

  

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