Daniel Nyga, M.Sc. (TUM)

daniel_nyga.jpg
Research Staff

Room: 1.77
Tel: –49 -421 218 64008
Fax: –49 -421 218 64047
Mail: nyga(at)cs[dot]uni-bremen[dot]de

About

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.

Fields of Interest

  • 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

Teaching

  • 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)

Supervised Theses

  • 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)

Publications

Journal Articles and Book Chapters
[1] Michael Beetz, Hagen Langer, Daniel Nyga, "Planning Everyday Manipulation Tasks--Prediction-based Transformation of Structured Activity Descriptions", Chapter in Exploring Cybernetics, Springer, pp. 63-83, 2015. [bib]
[2] Michael Beetz, Ferenc Bálint-Benczédi, Nico Blodow, Christian Kerl, Zoltán-Csaba Márton, Daniel Nyga, Florian Seidel, Thiemo Wiedemeyer, Jan-Hendrik Worch, "RoboSherlock: Unstructured Information Processing Framework for Robotic Perception", In Handling Uncertainty and Networked Structure in Robot Control, Springer International Publishing, Cham, pp. 181-208, 2015. [bib] [pdf] [doi]
Conference Papers
[3] Daniel Nyga, Michael Beetz, "Cloud-based Probabilistic Knowledge Services for Instruction Interpretation", In International Symposium of Robotics Research (ISRR), Sestri Levante (Genoa), Italy, 2015. [bib] [pdf]
[4] Daniel Nyga, Michael Beetz, "Reasoning about Unmodelled Concepts -- Incorporating Class Taxonomies in Probabilistic Relational Models", In Arxiv.org, 2015. Preprint [bib] [pdf]
[5] Gheorghe Lisca, Daniel Nyga, Ferenc Bálint-Benczédi, Hagen Langer, Michael Beetz, "Towards Robots Conducting Chemical Experiments", In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015. [bib] [pdf]
[6] Michael Beetz, Ferenc Balint-Benczedi, Nico Blodow, Daniel Nyga, Thiemo Wiedemeyer, Zoltan-Csaba Marton, "RoboSherlock: Unstructured Information Processing for Robot Perception", In IEEE International Conference on Robotics and Automation (ICRA), Seattle, Washington, USA, 2015. Best Service Robotics Paper Award [bib]
[7] Daniel Nyga, Ferenc Balint-Benczedi, Michael Beetz, "PR2 Looking at Things: Ensemble Learning for Unstructured Information Processing with Markov Logic Networks", In IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014. [bib] [pdf]
[8] Nicholas Hubert Kirk, Daniel Nyga, Michael Beetz, "Controlled Natural Languages for Language Generation in Artificial Cognition", In IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014. [bib] [pdf]
[9] Daniel Nyga, Michael Beetz, "Everything Robots Always Wanted to Know about Housework (But were afraid to ask)", In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vilamoura, Portugal, 2012. [bib] [pdf]
[10] Daniel Nyga, Moritz Tenorth, Michael Beetz, "How-Models of Human Reaching Movements in the Context of Everyday Manipulation Activities", In IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, 2011. [bib] [pdf]
[11] Moritz Tenorth, Daniel Nyga, Michael Beetz, "Understanding and Executing Instructions for Everyday Manipulation Tasks from the World Wide Web", In IEEE International Conference on Robotics and Automation (ICRA), Anchorage, AK, USA, pp. 1486-1491, 2010. [bib] [pdf]
Other Publications
[12] Moritz Tenorth, Daniel Nyga, Michael Beetz, "Understanding and Executing Instructions for Everyday Manipulation Tasks from the World Wide Web", Technical report, IAS group, Technische Universität München, Fakultät für Informatik, 2009. [bib]
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