Before I joined the Institute for Artificial Intelligence, I studied Computer Science at Technische Universität München, where I received my Master's degree in 2010 (with distinction). In February 2011 I started my PhD supervised by Prof. Michael Beetz at the Intelligent Autonomous Systems group at TUM, which I am now continuing at the IAI, University of Bremen.

I'm working on the import of action-specific knowledge from the World Wide Web into the knowledge bases of our mobile robots. In particular, my current research focuses on understanding natural language, in order to enable a robot to autonomously acquire new high-level skills by querying web pages such as eHow.com or wikiHow.com.

My work aims at building up action-specific knowledge bases from various knowledge sources, such as natural language, interactive computer games, observations of humans performing everyday activity or experience data of a robot.

Knowledge about actions and objects is represented as Probabilistic Robot Action Cores (PRAC), which can be thought of generic event patterns that enable a robot to infer important information that is missing in an original natural-language instruction. PRAC models are represented in Markov Logic Networks, a powerful knowlegde represenation formalism combing first-order logic and probability theory.

I am involved in the European research projects RoboHow (http://www.robohow.org) and ACAT.

I am also the lead developer in the projects pracmln and PRAC.

If you are interested in a student project in any of the above topics, please contact me via E-Mail or just drop into my office.

• Artificial Intelligence
• Probability Theory
• Probabilistic Knowledge Processing
• Machine Learning
• Statistical Relational Learning
• Data Mining/Knowledge Discovery
• Automated Learning/Understanding of WWW information
• Natural-Language Understanding

• AI: Knowledge Acquisition and Representation (WS2016/17) (Lecturer)
• AI: Knowledge Acquisition and Representation (WS2015/16) (Lecturer)
• Foundations of Artificial Intelligence (SS2015) (Tutorial/Co-Lecturer)
• AI: Knowledge Acquisition and Representation (WS2014/15) (Lecturer)
• Foundations of Artificial Intelligence (SS2014) (Tutorial)
• AI: Knowledge Acquisition and Representation (WS2013/14) (Co-Lecturer)
• Foundations of Artificial Intelligence (SS2013) (Tutorial)
• Technical Cognitive Systems (Lecture & Tutorial, at TUM) (SS2012)
• Techniques in Artificial Intelligence (Tutorial, at TUM) (WS2011/12)
• Discrete Probability Theory (Tutorial, at TUM) (SS2011)

• Lifelong Learning of First-order Probabilistic Models for Everyday Robot Manipulation (Master's Thesis, Marc Niehaus)
• Scaling Probabilistic Completion of Robot Instructions through Semantic Information Retrieval (Master's Thesis, Sebastian Koralewski)
• To see what no robot has seen before - Recognizing objects based on natural-language descriptions (Master's Thesis, Mareike Picklum)
• Web-enabled Learning of Models for Word Sense Disambiguation (Bachelor Thesis, Stephan Epping)
• Grounding Words to Objects: A Joint Model for Co-reference and Entity Resolution Using Markov Logic Networks for Robot Instruction Processing (Diploma Thesis, Florian Meyer)