Research

My research investigates how AI systems shape human behaviour — and how we can design them to support better decisions, healthier choices, trustworthy information environments, and societal benefit.

I work at the intersection of responsible AI, recommender systems, computational user behaviour, human-AI interaction, and data-driven media and health technologies. A central theme across my work is appropriate trust in AI: designing systems that users neither reject blindly nor trust uncritically, but understand, question, and use responsibly.

Much of my research focuses on AI systems that influence people’s information access, preferences, and everyday choices. This includes news recommender systems, AI-supported journalism, misinformation and trust, food and health recommender systems, behaviour change, and user-centred approaches to transparency, explanation, and accountability.

Research vision

My long-term research goal is twofold. First, I aim to deepen our understanding of online user behaviour by developing computational models, empirical methods, and responsible AI systems that can analyse, simulate, and predict behaviour in complex digital environments. Second, I aim to design and evaluate AI methods, interfaces, and interventions that can positively influence behaviour in societally important domains such as news consumption, health communication, and dietary decision-making.

Rather than treating AI as a purely technical optimisation problem, my research asks how AI systems interact with human cognition, values, institutions, and social contexts. This is particularly important in domains where recommender systems and personalization technologies do not merely predict preferences, but actively shape what people see, believe, choose, and trust.

Research approach

My work combines computational methods with behavioural theory and empirical evaluation. I draw on concepts and methods from computer science, information science, psychology, media studies, economics, health research, and human-computer interaction. Methodologically, my research includes offline experiments, simulations, user studies, living-lab studies, prototype evaluations, large-scale online experiments, and collaborations with industry and public-sector partners.

This interdisciplinary approach allows my group and collaborators to study AI systems not only in terms of algorithmic performance, but also in terms of user understanding, trust, behaviour change, societal implications, and real-world usefulness.

Core research areas

  • Responsible recommender systems: designing and evaluating recommender systems that support transparency, user agency, diversity, trust, and societal value.
  • AI, media, and democracy: studying how AI and personalization affect news consumption, misinformation, selective exposure, public knowledge, and trust in journalism.
  • Computational user behaviour: modelling, predicting, and interpreting how people interact with digital systems, platforms, recommendations, and AI-generated information.
  • Health, food, and behaviour change: developing AI and recommender systems that can support healthier choices, public health communication, and responsible decision-support.
  • Human-centred AI evaluation: studying how users understand, trust, question, and act on AI systems, explanations, labels, recommendations, and decision-support tools.

Grants

  • 2026: Research Council of Norway — CuratedAI: AI transparency, media literacy and appropriate media trust. Part of a combined 17.1 MNOK mobility project award connected to SFI MediaFutures and the University of Bergen. PI.
  • 2026: Research Council of Norway — VaccAI: Trustworthy health communication and vaccine beliefs in Norway and Ukraine. Part of a combined 17.1 MNOK mobility project award connected to SFI MediaFutures and the University of Bergen. PI.
  • 2024: Agenda Vestland — Reynir: Combatting misinformation with joined forces. Amount: 10,000,000 NOK, 2 years. Co-PI.
  • 2021: Research Council of Norway — The Double-edged Sword of News Recommenders’ Impact on Democracy (NEWSREC). Amount: 8,000,000 NOK, 4 years. Co-PI.
  • 2020: Research Council of Norway — MediaFutures: Research Centre for Responsible Media Technology & Innovation. Amount: approximately 26,000,000 EUR, 8 years. PI / Centre Director.
  • 2020: Alpro Foundation — Communicating the environmental impact of plant-based recipes. Amount: 49,000 EUR, 1 year. PI.
  • 2020: Research Council of Norway — RE-AIMED: Readjusted responses by use of AI in medical calls. Amount: 15,975,000 NOK, 4 years. PI.
  • 2019: European Union — Interdisciplinary connectivity: Understanding and managing complex systems using connectivity science. Amount: 4,030,279 EUR, 4 years. Co-Investigator.
  • 2018: Research Council of Norway — ITS for sustainable TRANSport: In-vehicle FEEDback on eco-driving and external costs. Amount: 6,700,000 NOK, 4 years. Co-Investigator.
  • 2018: Research Council of Norway — Investigating the impact of Artificial Intelligence on Journalism’s Social Contract: Issues of Machine Ethics in Modern Journalism. Amount: 297,000 NOK, 1 year. Co-Investigator.
  • 2017: Austrian Research Promotion Agency — EcoMove: Knowledge-based platform for predicting mobility bottlenecks and promoting sustainable behavioural change. Amount: 345,424 EUR, 2 years. Proposal Coordinator & Co-Investigator. I coordinated the proposal and developed the work package on predictive modelling and recommender systems.
  • 2017: European Union — ReTV: Enhancing and Repurposing TV Content. Amount: 3,100,000 EUR, 4 years. Co-Investigator. I helped shape the recommender systems and predictive modelling components of the proposal.
  • 2015: European Union — AFEL: Analytics for Everyday Learning. Amount: 2,581,940 EUR, 4 years. PI. I coordinated the project from the Know-Center side and developed work packages on visual analytics and social network analysis.
  • 2014: Austrian Research Promotion Agency — K1 Research Center Grant. Amount: 20,000,000 EUR, 8 years. Co-PI. I contributed significantly to the strategic research and financial plan for the Social Computing research area, including the involvement of industry partners.
  • 2014: Austrian Research Promotion Agency — Six COMET-funded industry projects. Amount: approximately 500,000 EUR, 1 year. PI. I co-acquired six industry projects in Social Computing with partners including major media and technology companies.
  • 2014: European Union — Marie Curie ERCIM Alain Bensoussan Fellowship. Amount: 50,000 EUR, 1 year. PI. The fellowship supported research on predictive modelling in big data at NTNU in Norway.
  • 2013: Austrian Research Promotion Agency — Three COMET-funded industry projects. Amount: approximately 250,000 EUR, 1 year. PI. I co-acquired three industry projects in Social Computing.
  • 2012: Austrian Research Promotion Agency — Innovation Check Grant. Amount: 5,000 EUR, 1 year. PI. The project explored social recommender systems on multi-dimensional data together with an Austrian start-up.
  • 2012: Marshall Plan Foundation — Visiting Scholar Fellowship. Amount: 7,500 USD, 5 months. PI. The fellowship supported research on efficient information access in social systems.
  • 2011: Austrian Research Promotion Agency — Dissertation Fellowship. Amount: 100,000 EUR, 2 years. PI. The project focused on tag-based information access in social systems.

Awards & Distinctions

  • 2023: Best Paper Award Honorable Mention at ACM DIS 2023 for “Designing for Control in Nurse-AI Collaboration During Emergency Medical Calls.”
  • 2020: ACM Senior Member, awarded for technical leadership and sustained professional contributions.
  • 2020: Momentum Stipend, University of Bergen. UiB’s flagship development programme for early-career researchers pursuing an academic careers at a research university. Amount: 100,000 NOK.
  • 2018: Austrian Chamber of Commerce Prize for the proposal “A predictive Facebook advertising model for the Austrian food retail trade.”
  • 2017: ACM Computing Reviews — Best of Computing for “VizRec: Recommending Personalized Visualizations,” published in ACM Transactions on Interactive Intelligent Systems.
  • 2017: Best Paper Award Honorable Mention at The Web Conference, WWW 2017, for “Investigating the Healthiness of Internet-Sourced Recipes: Implications for Meal Planning and Recommender Systems.”
  • 2014: Best Poster Award at the ACM Conference on Hypertext and Social Media, HT 2014, for “TagRec: Towards A Standardized Tag Recommender Benchmarking Framework.”
  • 2014: Among the Best Papers at WWW Companion 2014 for “Long Time No See: The Probability of Reusing Tags as a Function of Frequency and Recency.”
  • 2013: Among the Best Papers at IEEE/ACM ASONAM 2013 for “Acquaintance or Partner? Predicting Partnership in Online and Location-based Social Networks.”
  • 2013: Best Paper Award at the International Conference on Social Eco-Informatics, SOTICS 2013, for “Predicting Social Interactions from Different Sources of Location-based Knowledge.”
  • 2013: Best Poster Award at the ACM Web Science Conference, WebSci 2013, for “Head Start: Improving Academic Literature Search with Overview Visualizations based on Readership Statistics.”
  • 2012: Best Paper Award at the International Conference on Knowledge Management and Knowledge Technologies, I-Know 2012, for “Exploring the Differences and Similarities of Hierarchical Decentralized Search and Human Navigation in Information-networks.”
  • 2012: Douglas Engelbart Best Paper Nomination at the ACM Conference on Hypertext and Social Media, HT 2012, for “Evaluating Tag-Based Information Access in Image Collections.”
  • 2012: ACM Student Travel Award to attend the ACM Conference on Hypertext and Social Media, HT 2012, Milwaukee, USA.
  • 2011: Young Scholar Best Paper Award at the International Conference on Information Technology Interfaces, ITI 2011, for “Improving the Navigability of Tagging Systems with Hierarchically Constructed Resource Lists: A Comparative Study.”
  • 2010: Best Paper Nomination at IEEE SocialCom 2010 for “On the Navigability of Social Tagging Systems.”
  • 2010: SFG & OFG International Travel Award from the Austrian Science Funds SFG and OFG.