Delia Rusu

Google Scholar

I am a lead data scientist specialized in applications of machine learning and natural language processing to social sciences and fintech.


Previously, I was a doctoral researcher at the Jozef Stefan Institute, Artificial Intelligence Laboratory. My research areas were Text Mining, Computational Linguistics, Semantic Web.

I defended my PhD thesis Text Annotation Using Background Knowledge in 2014.


Estimating stock price correlations using Wikipedia. At PyData London 2016 I analysed the FTSE 100 companies while at PyData Berlin 2016 I analyzed the DAX companies. [GitHub repository][Data Skeptik podcast]

Detecting novel anomalies in Twitter, a talk at PyData London 2016. [GitHub repository]

Text Stream Processing, a tutorial held together with Prof. Dr. Dunja Mladenic at the International Conference on Web Intelligence, Mining and Semantics (WIMS) 2012 [slides]

Selected Publications

Rusu, D., Fortuna, B. and Mladenic, D. 2014. Measuring Concept Similarity in Ontologies using Weighted Concept Paths. Applied Ontology 9, no. 1, pp. 65--95.

Rusu, D., Hodson, J. and Kimball, A. 2014. Unsupervised Techniques for Extracting and Clustering Complex Events in News. Second Workshop on EVENTS: Definition, Detection, Coreference and Representation, 52nd Annual Meeting of the Association for Computational Linguistics (ACL). Baltimore, MD, USA.

Rusu, D., Fortuna, B. and Mladenic, D. 2011. Automatically Annotating Text with Linked Open Data. 4th Linked Data on the Web Workshop (LDOW), 20th World Wide Web Conference (WWW). Hyderabad, India.

EU Projects

RENDER - Reflecting Knowledge Diversity was a Specific Targeted Research Project (STREP) which aimed at discovering, managing and representing information on the Web through diversity-aware algorithms.


Enrycher is a service-oriented platform for enhancing text.