- Nov 10, 2023: Best Paper Award (1000 USD) for SemOpenAlex at ISWC'23.
- April 27, 2023: Our workshop at the Girls' Day with reserved GPU Cluster: AI & Language Models
- 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: Research stay/guest professorship at the Digital Science Center (DiSC), University of Innsbruck.
- Jul 12, 2022: NAACL Paper: Few-Shot Document-Level Relation Extraction
Michael Färber on
- his personal website (incl. CV and list of publications),
- Google Scholar,
- Wikidata (Scholia, Reasonator),
- Semantic Scholar,
Profile: As W3 Deputy Full Professor until 2025, I am the head of the research group Web Science at the Karlsruhe Institute of Technology (KIT). Together with my team of seven PhD students and one postdoc, I work on the development and application of artificial intelligence (AI) methods. Specifically, my focus is in the triangle of knowledge representation, machine learning, and natural language processing. Since my postdoc phase, I have made it my mission to find solutions to the increasingly urgent problem of the rising flood of information in science (see "tsunami of publications") and to develop novel methods of communication in science. To this end, I conduct research on the extraction and modeling of scientific knowledge, in particular on the construction of large knowledge graphs. I am also developing search and recommendation systems that can exploit the explicitly modeled knowledge while explaining the results and recommendations to the user. I have published more than 80 papers in prestigious international conferences (e.g., CIKM, ISWC, ECIR, NAACL) with international researchers. In addition, I am leading several projects (e.g. TruthfulLM, ChemKB, IIDI, KIGLIS, KIWI) as Principal Investigator (PI) at the KIT Institute AIFB.
- natural language processing,
- machine learning, and
- knowledge representation (e.g., knowledge graphs).
Among other things, Michael Färber pursues research on scholarly data mining (e.g., scientific impact quantification), scholarly recommender systems (e.g., recommending citations, papers, data sets, and neural networks), and scholarly knowledge graphs (e.g., modeling papers, authors, methods, and datasets). Furthermore, he develops AI solutions for peace mediation (see AI4Peace).
More information can be found at his homepage and on Google Scholar.
Online Demo Systems
Recently developed demonstration systems:
- RefBee: http://refbee.org/
- ...shows for an author which publications are in which bibliographic databases.
- C-Rex: http://c-rex.org
- ... recommends citations for given texts.
- PaperHunter: http://paperhunter.net
- ... provides, among other things, the sentences in which searched papers are cited.
- ScholarSight: http://scholarsight.org
- ... allows the exploration of trends from scientific concepts.
- Linked Crunchbase: http://linked-crunchbase.org
- ... allows to query information about startups and innovative companies in the Semantic Web format RDF.
Recently created data sets:
- DSKG: http://dskg.org
- ...a knowledge graph representing datasets.
- unarXive: http://unarxive.org
- ... contains the full texts of all papers on arXive.org with further annotations.
- Microsoft Academic Knowledge Graph: https://makg.org
- ... a knowledge graph containing the metadata of almost all publications in all scientific disciplines.
- FAIRnets: https://doi.org/10.5281/zenodo.3885249
- ...a knowledge graph with metadata about neural networks.
Code, Data, and Presentations
Open Positions and Theses
Open student assistant jobs (Hiwis)
- in machine learning, natural language processing, or knowledge graphs: 
- in Semantic MediaWiki or PHP: .
Current calls for Bachelor/Master thesis
|Thema4864||Quantum Computing for Natural Language Processing|
|Thema4977||Knowledge Graphs for Robots’ Situational Awareness|
|Thema4420||Wie fair sind Forscher? Eine Analyse von Zerrungen bzgl. Zitaten in wissenschaftlichen Publikationen|
|Thema4909||Scalable Graph Neural Networks on Knowledge Graphs|
|Thema4910||Performance Analysis of Graph Neural Diffusion via Fourier Decomposition|
|Thema4648||Creating a Large Knowledge Graph about Scientific Publications for Innovation Forecast|
|Thema4574||Deep Learning + Knowledge Graphs|
|Thema4772||GPT-3, BERT & Co.: When to use which language model?|
|Thema4423||Automatically Recommending Citations for Texts Using Neural Networks|
I have supervised more than 50 Bachelor/Master theses (➜ List of all completed theses directly supervised).
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, USA) and funded by the DAAD. More information under Web_Science/DAAD-Stipendium/en.
- 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