Prof. Dr.-Ing. Michael Färber

Professor for Scalable Software Architectures and Data Analytics

Contact Information

Phone: +49 721 608 465 92
E-Mail: michael.faerber@tu-dresden.de
Office: Strehlener Str. 12-14, Room 738

Consultation hours by appointment.

Profile

Michael Färber has been a full professor (W3) for Scalable Software Architectures for Data Analytics at the AI Center ScaDS.AI, TU Dresden since April 2024. Previously, he led the Web Science research group at Karlsruhe Institute of Technology (KIT) from October 2020 to March 2024. His research interests focus on knowledge representation, machine learning, and natural language processing. Among other topics, he aims to tackle the challenge of the rising flood of information in science by extracting information from scientific papers and developing advanced search and recommender systems.

News and Achievements

• April 1, 2024: Starting as full professor (W3) at ScaDS.AI/TU Dresden.
• Nov 10, 2023: Best Paper Award (1000 USD) for SemOpenAlex at ISWC’23.
• April 27, 2023: Hosted a workshop at Girls‘ Day, featuring AI & Language Models with a reserved GPU Cluster.
• Feb – Mar, 2023: Research stay at the NII (Tokyo).
• Oct 27, 2022: Best Poster award (300 USD) for The Green AI Ontology at ISWC’22.
• Aug 01 – Sep 30, 2022: Guest professorship at the Digital Science Center (DiSC), University of Innsbruck.
• Jul 12, 2022: Published a paper on Few-Shot Document-Level Relation Extraction at NAACL.

Online Presence

• Personal Website (includes CV and list of publications)
• Google Scholar
• DBLP
• Wikidata (Scholia, Reasonator)
• ORCID
• ResearchGate
• Semantic Scholar
• YouTube

Online Demo Systems

Explore Prof. Färber’s recent demonstration systems:

• RefBee: http://refbee.org/ – Tracks publications across bibliographic databases.
• C-Rex: http://c-rex.org – Recommends citations for texts.
• PaperHunter: http://paperhunter.net – Searches citation contexts in papers.
• ScholarSight: http://scholarsight.org – Explores scientific concept trends.
• Linked Crunchbase: http://linked-crunchbase.org – Queries startup and innovation data in RDF format.

Data Sets

• DSKG: http://dskg.org – A knowledge graph of datasets.
• unarXive: http://unarxive.org – Contains annotated full texts from arXive.org.
• Microsoft Academic Knowledge Graph: https://makg.org – Metadata of publications across disciplines.
• FAIRnets: https://doi.org/10.5281/zenodo.3885249 – Metadata about neural networks.

Open Positions and Theses

Open student assistant jobs (SHKs)

• In graph-based machine learning.
• In machine learning, natural language processing, or knowledge graphs.

Current calls for Bachelor/Master thesis

• Please ask!

Prof. Färber has supervised over 50 Bachelor and Master theses and encourages both English and German-speaking students to apply. Many thesis topics are available for study abroad through partner institutions and DAAD funding.