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 works in the area of explanations and explanation interfaces. She studies how to best select, present, and adapt the presentation of information (using both natural language generation, and visualizations) in artificial advice giving systems.

She is interested in tackling issues regarding responsible data analytics, algorithmic transparency, diversity, 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 intelligent user interfaces.

Track record: Dr Tintarev has published over 40 peer reviewed papers. H-index: 15, most cited article >250 citations, > 1200 total (according to Google scholar on the 27/06/18), on the topic of personalized information presentation in different application areas. 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.

Teaching: In 2018 she is co-teaching two Master courses: Information Retrieval (NLP) with Claudia Hauff; and Crowd Computing (HCI) with Alessandro Bozzon.

Academic service: Dr. Tintarev is a senior PC member for the following conferences: She additionally reviews for many leading conferences and journals in human-computer interaction (CHI), artificial intelligence (IJCAI-ECAI), and personalization (TiiS). She also serves in organizational roles for international conferences and workshops. Dr. Tintarev examines PhD dissertations, and reviews grant proposals in the Netherlands (NWO), the UK (EPSRC), and Belgium (VLAIO).


12th of July Full paper accepted to Recsys with Yucheng Jin and Katrien Verbert: Effects of Personal Characteristics on Music Recommender Systems with Different Levels of Controllability

27th of June Great turn out (~100 registrations) for our Delft Data Science event on Trusted Data Analytics. Speaker profiles and presentations here.

18th of June. Paper accepted to SIGIR workshop on ExplainAble Recommendation and Search (EARS): Explaining Credibility in News Articles using Cross-Referencing, with Dimitrios Bountouridis, Monica Marrero, and Claudia Hauff.

4th of June. Joined the Delft Design for Values Management team. DDFV's mision is to bring together, integrate, and expand existing practices and expertise at Delft University of Technology in the field of design for values. In this role, I am excited to share lessons learned within design for Responsible Data Science, and learn from colleagues about best practices in other departments at our university.

18th of May. Congratulations to PhD candidate Shabnam Najafian for her paper accepted to UMAP Late breaking results: Generating Consensus Explanations for Group Recommendations.

16th of May. Paper accepted to UMAP workshop on Fairness in User Modeling, Adaptation and Personalization: Same, Same, but Different: Algorithmic Diversification of Viewpoints in News, with Emily Sullivan, Dror Guldin, Sihang Qiu, Daan Odjik, Reza Aditya Permadi, and Andreas Christian Pangaribuan

19th of April. Summary of The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction, with Ferro et al, accepted for publication in the SIGIR Forum (June)!

13th of April. Effects of Individual Traits on Diversity-aware Music Recommender User Interfaces, full paper accepted to UMAP. With Yucheng Jin and Katrien Verbert

16th of February. New paper: Adrian Holzer, Nava Tintarev, Samuel Bendahan, Shane Greenup, and Denis Gillet. Digitally Scaffolding Debate in the Classroom. Proceedings of the 2018 CHI Conference Extended Abstracts on Human Factors in Computing Systems.

12th of December. New book chapter with Alexander Felfernig, Thi Ngoc Trang Tran, and Martin Stettinger: Explanations for Groups, in handbook on Group Recommender Systems, Springer.

20th of November. Paper accepted to Symposium on Applied Computing (SAC), Recommender Systems Track, Knowing the Unknown: Visualising Consumption Blind-Spots in Recommender Systems, with Shahin Rostami and Barry Smyth.