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* [http://www.aifb.kit.edu/web/Michael_F%C3%A4rber2 Abstract of Michael Färber's AIFB Colloquium talk about his PhD topic]

Version vom 17. Dezember 2016, 18:33 Uhr

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Michael Färber is the deputy professor (W3) of the research group Web Science at the KIT-institute AIFB since October 1, 2020.


Research

Michael's research interests:

  • natural language processing,
  • machine learning, and
  • knowledge representation (e.g., knowledge graphs).


Current research foci:


More information can be found at his homepage and on Google Scholar.

Recently developed demonstration systems:


Recently created data sets:



Open Positions and Theses

Open student assistant job (Hiwi) in the area of machine learning, natural language processing, and/or Semantic Web technologies: [1]
Michael Färber has supervised around 40 Bachelor/Master theses. Current calls for Bachelor/Master thesis:

 Titel
Thema4420Wie fair sind Forscher? Eine Analyse von Zerrungen bzgl. Zitaten in wissenschaftlichen Publikationen
Thema4421Implementing an Approach for Linking Text to the Knowledge Graph Wikidata
Thema4423Automatically Recommending Citations for Texts Using Neural Networks
Thema4554Google, Microsoft, & Co. – How Big is the Influence of Enterprises on Computer Science Research?
Thema4574Deep Learning + Knowledge Graphs
Thema4742Übersicht über aktuelle Forschung zu Verzerrungen in der Wissenschaft

All topics are open to English and German-speaking students.
Many of the thesis topics can also be written at a partner institution abroad (e.g. in Japan, Italy, France) and funded by the DAAD, given that the application is made one year in advance. More information under Web_Science/DAAD-Stipendium/en.



Publications
Publications


Talks
Talks


Active Projects
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AI in Peacemaking
External Link: https://mediatingmachines.com/

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DataScore
External Link: https://datascore.int.kit.edu/

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digilog@bw
External Link: https://digilog-bw.de

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KIGLIS

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ProData
External Link: http://www.pro-data.org

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TransPer


Research area
Semantic Search, Knowledge Representation And Reasoning, Machine Learning, Text Mining, Semantical Annotation, Information Extraction, Natural Language Processing, Digital Libraries, Knowledge Discovery, Data Mining, Artificial Intelligence, Data Science, Semantic Web, Trustworthy AI


KIT Functions and Competence Field

Cognition and Information Engineering