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Dr. Michael Färber
- Substitute Professor
- Phone: +49 721 608 465 92
- Email: michael faerber∂kit edu
- Room: 5A-15 (Building: 05.20)
- Research Group: Web Science
- vCard
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:
- scholarly data mining and
- AI4Peace.
More information can be found at his homepage and on Google Scholar.
Recently developed demonstration systems:
- PaperHunter: http://paperhunter.net
- ScholarSight: http://scholarsight.org
- Linked Crunchbase: http://linked-crunchbase.org
Recently created data sets:
- unarXive: http://unarxive.org
- Microsoft Academic Knowledge Graph: http://ma-graph.org
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 | |
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Thema4420 | Wie fair sind Forscher? Eine Analyse von Zerrungen bzgl. Zitaten in wissenschaftlichen Publikationen |
Thema4421 | Implementing an Approach for Linking Text to the Knowledge Graph Wikidata |
Thema4423 | Automatically Recommending Citations for Texts Using Neural Networks |
Thema4554 | Google, Microsoft, & Co. – How Big is the Influence of Enterprises on Computer Science Research? |
Thema4574 | Deep Learning + Knowledge Graphs |
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.
External Link: https://mediatingmachines.com/ |
External Link: https://datascore.int.kit.edu/ |
External Link: https://digilog-bw.de |
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External Link: http://www.pro-data.org |
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- 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