Dr. Nava Tintarev is an Assistant Professor and Delft Technology Fellow in the Web Information Systems group, Faculty of Electrical Engineering, Mathematics and Computer Science at TU Delft. She studies how to best present and adapt the presentation of complex data (using both natural language generation, and visualizations) in artificial advice giving systems.

The ENSURE (ExplaiNing SeqUences in REcommendations) project looks at ways of improving the transparency and decision support for recommender systems (like Amazon and Spotify), in recommendation scenarios that contain both surprising recommendations and trade-offs. She is also leading a smaller project looking at issues relating to critical thinking in higher education: SuSPECT: Scaffolding Student PErspectives for Critical Thinking. She is interested in tackling issues regarding ethics in big data, algorithmic transparency, fake news, and filter bubbles.

Nava was previously an assistant professor at Bournemouth University (UK), a research fellow at Aberdeen University (UK), and a research engineer for Telefonica Research (Spain).

Relevant keywords: explanations, natural language generation, human-computer interaction, personalization (recommender systems), and visualization.

Track record: Dr Tintarev has published in peer-reviewed venues on the topic of personalized information presentation in different application areas, including Recommender Systems, Scrutable Autonomous Systems (SAsSy), nature conservation (MinkApp), and Augmentative and Alternative Communication (AAC) ("How was school today...?"). In the last 2 years she has received grant awards as PI or Co-I totalling over €200K. She has been a member of the ACM since January 2014.

Academic service: Dr. Tintarev is a senior PC member for the following conferences: She also reviews for other leading conferences and journals, as well as serves in organizational roles for international conferences and workshops. Dr. Tintarev examines PhD dissertations, and reviews grant proposals as a full member of the EPSRC College.


10th of August. Poster accepted to SEMANTiCS 2017: Mengmeng Ye, Christoph Lofi, and Nava Tintarev. "Memorability of semantically grouped online reviews".

18th of July. Paper accepted to the FATREC Workshop on Responsible Recommendation, in association with Recsys'17: Presenting Challenging Recommendations: Making Diverse News Acceptable.

17th of July. Case study with Blendle accepted to NWO ICT with Industry on Personalized (and diverse) news selection. Seeking PhD students and Postdocs. November 27 - December 1, 2017.

10th of July. Paper accepted with Christoph Lofi at the Complex-Rec workshop: Towards Analogy-based Recommendation: Benchmarking of Perceived Analogy Semantics.

5th of July. Invited to attend the Royal Society's workshop on filter bubbles on the 19 July!

5th of July. I am excited to be giving a keynote at the workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP) in conjunction with UMAP 2017.

5th of July. Approved grant proposal: Designing Artificial Advice Givers that Consider Perspective and Affect in Reasoning. Funded by the Delft Design for Values Open Subsidy.

5th of July. Our position paper (with Pavel Kucherbaev, and Carlos Rodriguez) ``Ephemeral Context to Support Robust and Diverse Recommendations'' has been accepted to appear at the Machine Learning for Music Discovery workshop at ICML 2017.

14th of June. Delighted to be joining the Dagstuhl Perspectives Workshop, ``Towards Cross-Domain Performance Modeling and Prediction: IR/RecSys/NLP'' later this year.