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).
explanations, natural language generation, human-computer interaction, personalization (recommender systems), and intelligent user interfaces.
Dr Tintarev has published
around 50 peer reviewed papers. H-index: 16, most cited article ~300 citations, > 1300 total (according to Google scholar on the 30/07/18), on the topic of personalized information presentation in different application areas. She has been a member of the ACM since January 2014.
In 2018 she is co-teaching two Master courses: Information Retrieval (NLP) with Claudia Hauff
; and Crowd Computing (HCI) with Alessandro Bozzon
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).
30th of July.
It's official! We are one of two teams working with Twitter on measuring conversational health (2/230 proposals accepted) . Official Twitter announcement
. Official TU Delft announcement
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 (17% acceptance rate)
27th of June.
Great turn out (~100 registrations) for our Delft Data Science event on Trusted Data Analytics. Speaker profiles and presentations
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 mission 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