Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
team:daniel_nyga [2017/06/16 11:46] – [Fields of Interest] nyga | team:daniel_nyga [2017/08/30 08:29] – [Supervised Theses] nyga | ||
---|---|---|---|
Line 2: | Line 2: | ||
=====Dr.rer.nat. Daniel Nyga====== | =====Dr.rer.nat. Daniel Nyga====== | ||
| {{: | | {{: | ||
- | |::: ||Research Staff\\ \\ || | + | |::: ||Postdoctoral Researcher\\ \\ || |
|:::|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: |< | |:::|Mail: |< | ||
Line 53: | Line 53: | ||
====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, | + | 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, |
He was involved in the European FP7 research projects [[http:// | He was involved in the European FP7 research projects [[http:// | ||
Line 90: | Line 90: | ||
* To see what no robot has seen before - Recognizing objects based on natural-language descriptions (Master' | * To see what no robot has seen before - Recognizing objects based on natural-language descriptions (Master' | ||
* Web-enabled Learning of Models for Word Sense Disambiguation (Bachelor Thesis, Stephan Epping) | * 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) | + | * 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 ====== | ||
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
Discover our VRB for innovative and interactive research
Memberships and associations: