Short Curriculum Vitae

Cyrill Stachniss is currently a lecturer at the University of Freiburg in Germany. Until September 2010, he had a 1-year full professor position during the sabbatical of Wolfram Burgard and was heading the lab for Autonomous Intelligent Systems in Freiburg. Cyrill Stachniss finished bis habilitation in November 2009 after working as an academic advisor at the University of Freiburg and being a guest lecturer at the University of Zaragoza in Spain. Before that, he was a senior researcher at the Swiss Federal Institute of Technology in the Autonomous Systems Lab of Roland Siegwart. In April 2006, he finished his PhD thesis entitled "Exploration and Mapping with Mobile Robots", supervised by Wolfram Burgard, at the Department of Computer Science at the University of Freiburg. Before being a PhD student, he studied physics ("Vordiplom"/B.Sc.) and computer science ("Diplom"/M.Sc.) at the University of Marburg and Freiburg. Since 2008, he is an associate editor of the IEEE Transactions on Robotics and since 2010 a Microsoft Research Faculty Fellow. In his research, he focuses on probabilistic techniques in the context of mobile robotics, perception, and navigation problems. He is also interested in classification and learning approaches, in computer controlled cars, and in computer vision. See my publication list and research page for further details.

You can also find a detailed resume here.

Awards

  • Microsoft Research Faculty Fellow (2010).
  • 7th EURON Georges Giralt Award for the best robotics thesis in Europe in 2006 (received in 2008).
  • Wolfgang-Gentner PhD Award (2006)
    for my PhD thesis Exploration and Mapping with Mobile Robots .
  • ICRA 2005 -- Finalist best student paper (2005)
    for the paper Supervised Learning of Places from Range Data using AdaBoost.
  • ICASE-IROS 2004 best paper award on application (2005)
    for the paper Grid-based FastSLAM and Exploration with Active Loop Closing.
  • Award of the German Engeneering Society, VDI (2003) for my master's thesis Zielgerichtete Kollisionsvermeidung fuer mobile Roboter in dynamischen Umgebungen.