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 fake news in education and problem-based learning: SuSPECT: Scaffolding Student PErspectives for Critical Thinking. She is currently interested in contributing to projects and grant applications 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).
explanations, natural language generation, human-computer interaction, personalization (recommender systems), and visualization.
I have 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
), and Augmentative and Alternative Communication (AAC)
("How was school today...?")
. Sometimes external organizations give me money
to do interesting work. I have been a member of the ACM since January 2014.
I am a senior PC member for the Conference on User Modeling, Adaptation and Personalization
ACM Conference on Recommender Systems
. I have also reviewed for other leading conferences and journals
, as well as served in organizational roles
for international conferences and workshops. I examine PhD dissertations and review grant proposals (e.g., for the EPSRC).
I am on the outlook for enthusiastic PhD
and Masters students
to work on topics relating to the transparency of intelligent systems, and usability/interface issues (e.g. diversity, novelty) in recommender systems.
22nd of March
4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS'17
), accepted to the ACM Recommender Systems Conference and first call for papers
21st of March.
Looking forward to Recsys.NL hosted by XITE Networks, where I'll be giving a talk titled ``Explain yourself! Arguing with Recommender Systems.''. Join us and sign up to the Meetup here
23rd of Feb. I'm hiring!
2 year postdoc on explanations in recommender systems at TU Delft.
23rd of Feb.
Opinion piece for DIGIT on
Ethics in Data Analytics: Balancing Insight and Privacy
11th of Feb.
Joining the Web Information Systems group
, Faculty of Electrical Engineering, Mathematics and Computer Science TU Delft as an assistant professor on a personal fellowship.
24th of November:
I am delighted to act as track chair for the Intelligent User Interfaces track at UMAP'17, and as senior PC member for Recsys'17.
12th of November:
Chairing a panel on ``Data Analytics: Balancing Insight, Privacy & Trust'' at the Big Data Conference
, Dynamic Earth, Edinburgh, 8th of December, 2016
2nd of November:
Our introduction to the special issue on Human Interaction With Artificial Advice Givers
in ACM TiiS has been accepted. Articles will be available here
31st of October:
Our paper, Effects of Individual Differences in Working Memory on Plan Presentational Choices
has been accepted for publication in Frontiers in Psychology, section Human-Media Interaction (IF: 2.463).