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team:daniel_nyga [2017/06/16 08:28] – [About] nygateam:daniel_nyga [2017/06/29 08:20] – [Dr.rer.nat. Daniel Nyga] nyga
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 =====Dr.rer.nat. Daniel Nyga====== =====Dr.rer.nat. Daniel Nyga======
 | {{:wiki:daniel_nyga.jpg?0x180}} |||| | {{:wiki:daniel_nyga.jpg?0x180}} ||||
-|::: ||Research Staff\\ \\ ||+|::: ||Research Associate\\ \\ ||
 |:::|Room: |1.77| |:::|Room: |1.77|
-|:::|Tel: |--49 -421 218 64008|+|:::|Tel: |--49 -421 218 64010|
 |:::|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>|
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 ====Dissertation==== ====Dissertation====
-[[http://nbn-resolving.de/urn:nbn:de:gbv:46-00105882-13|{{:team:cover.png?200 |}}]]A robot that can be simply told in natural language what to do -- this +[[http://nbn-resolving.de/urn:nbn:de:gbv:46-00105882-13|{{:team:cover.png?200 |}}]]//Abstract//-- A robot that can be simply told in natural language what to do -- this 
 has been one of the ultimate long-standing goals in both Artificial  has been one of the ultimate long-standing goals in both Artificial 
 Intelligence and Robotics research. In near-future applications,  Intelligence and Robotics research. In near-future applications, 
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 vagueness and ambiguity in natural language and infer missing  vagueness and ambiguity in natural language and infer missing 
 information pieces that are required to render an instruction  information pieces that are required to render an instruction 
-executable by a robot. To this end, \prac formulates the problem of +executable by a robot. To this end, PRAC formulates the problem of 
 instruction interpretation as a reasoning problem in first-order  instruction interpretation as a reasoning problem in first-order 
 probabilistic knowledge bases. In particular, the system uses Markov  probabilistic knowledge bases. In particular, the system uses Markov 
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 ====Projects==== ====Projects====
-Daniel Nyga's research interests revolve around topics on Artificial Intelligence and Data Science in general, as well as Machine Learning, Data Mining and Pattern Recognition techniques. In particular, he is interested in probabilistic graphical and relational knowledge representation, learning and inference methods.+Daniel Nyga's research interests revolve around topics on Artificial Intelligence and Data Science in general, as well as Machine Learning, Data Mining and Pattern Recognition techniques. In particular, he is interested in probabilistic graphical and relational knowledge representation, learning and inference methods, and in applications thereof in natural-language understanding, knowledge processing and robotics.
  
 He was involved in the European FP7 research projects [[http://www.robohow.org|RoboHow]] and [[http://www.acat-project.eu|ACAT]]. He was involved in the European FP7 research projects [[http://www.robohow.org|RoboHow]] and [[http://www.acat-project.eu|ACAT]].
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 He is the lead developer in the projects [[http://www.pracmln.org|pracmln]] and [[http://www.actioncores.org/|PRAC]]. He is the lead developer in the projects [[http://www.pracmln.org|pracmln]] and [[http://www.actioncores.org/|PRAC]].
  
-His GitHub profile can be found [[http://www.github.com/danielnyga|here]]+His GitHub profile can be found [[http://www.github.com/danielnyga|here]].
  
  
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   * Data Mining/Knowledge Discovery   * Data Mining/Knowledge Discovery
   * Automated Learning/Understanding of WWW information   * Automated Learning/Understanding of WWW information
-  * Natural-Language Understanding+  * Natural-language understanding
  
 ====Teaching==== ====Teaching====
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