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team:daniel_nyga [2013/06/25 08:18] – created pmaniateam:daniel_nyga [2013/09/25 05:32] – [Fields of Interest] nyga
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-=====Daniel Nyga======+=====Daniel Nyga, M.Sc. (TUM)======
 ^ {{:wiki:daniel_nyga.jpg}} |||| ^ {{:wiki:daniel_nyga.jpg}} ||||
 |::: ||Research Staff\\ \\ || |::: ||Research Staff\\ \\ ||
 |:::|Room: |1.77| |:::|Room: |1.77|
-|:::|Tel: |--49 -421 218 64039|+|:::|Tel: |--49 -421 218 64008|
 |:::|Fax: |--49 -421 218 64047| |:::|Fax: |--49 -421 218 64047|
 |:::|Mail: |<cryptmail>nyga@cs.uni-bremen.de</cryptmail>| |:::|Mail: |<cryptmail>nyga@cs.uni-bremen.de</cryptmail>|
 |:::| || |:::| ||
  
-====== About ======+====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. 
 + 
 +{{research:actioncore.png?w=620&h=65&t=1357297411}} 
 + 
 +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. 
 + 
 +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==== 
 +  * Foundations of Artificial Intelligence ([[https://ai.uni-bremen.de/teaching/kiss2013|SS2013]]) (Tutorial) 
 +  * Technical Cognitive Systems (Lecture & Tutorial, @TUM) ([[https://ias.cs.tum.edu/teaching/ss2012/techcogsys|SS2012]]) 
 +  * Techniques in Artificial Intelligence (Tutorial, @TUM) ([[https://ias.cs.tum.edu/teaching/ws2011/240927786|WS2011/12]]) 
 +  * Discrete Probability Theory (Tutorial, @TUM) ([[http://www14.in.tum.de/lehre/2011SS/dwt/|SS2011]]) 
 + 
 +====Supervised Theses==== 
 +  * 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 ====== ====== Publications ======
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Prof. Dr. hc. Michael Beetz PhD
Head of Institute

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