Dr Danica Damljanovic is an Artificial Intelligence (AI) and Natural Language Processing (NLP) expert.

Short Bio
Danica received her PhD in AI on the topic of Natural Language Interfaces for Querying Ontologies from the University of Sheffield in 2011. It was here that Danica developed the FREyA system which was scored as the best question answering system against the DBpedia knowledge base (structured Wikipedia) in the QALD-1 Challenge 2011. Her interests have always been transitioning cutting edge research methods into practical applications. She received a BSc and MSc in AI from University of Belgrade in 2003 and 2007 respectively, on the topics of expert systems and ontology reasoning as a way to improve users’ experience in tourism portals. 

Danica started her career as a software engineer, and has, in parallel, researched various areas of AI, mainly focusing on NLP, dialogue systems, topic detection, semantic web, ontologies, question answering systems, and conversational agents. She is an internationally recognized scientist and has published numerous publications in high impact journals and conferences. She has been an invited speaker, and a member of prestigious program committees for conferences and journals in AI related fields. Danica works as Head of Language Science in RecordSure. She has been involved in few cutting-edge projects and worked with SRI on a new-generation Virtual Personal Assistant technology as a part of her role in Kuato Studios.

Before joining Kuato Studios, Danica was a research scientist at the University of Sheffield in the Natural Language Processing Group. While there, Danica worked as a lead researcher and vice-coordinator on several EC-funded projects including TAO STREP for which she developed tools for ontology-based annotation and Natural Language Interfaces for querying ontologies. She was a Package leader in the EC-funded IP LarKC project, where she coordinated the research group of five project partners worldwide. The goal of the group was to implement novel approaches that would enable reasoning at the Web-scale, by applying Information Retrieval, Machine Learning and Cognitive Science methods.

Beyond work, Danica loves socialising, sports (rollerblading, skiing, tennis, swimming, running, ...), adventure, dancing tango, and travelling. Mens sana in corpore sano.

Member of GOOD OLD AI research network. 

Subpages (1): Data Science