I am a Senior Postdoctoral Researcher at the Applied Software Engineering & AI Group, Institute of Software Engineering and Artificial Intelligence, Graz University of Technology (TU Graz), Austria.
A central theme in my research is how people actually experience a recommendation or an explanation, not just whether it is technically correct. I design explanation and recommendation strategies that adapt to human factors — user characteristics, demographics, situational context, and cognitive style — rather than treating every user the same way. These solutions support decision-making for both individual users and groups of users. I extend this human-centered perspective to AI systems more broadly, including those built on Large Language Models, with the goal of keeping decision support trustworthy, fair, and aligned with the people who rely on it.
Beyond explaining recommendations, I also work on explanation approaches for constraint-based systems. Here, explanations take the form of conflicts — sets of user requirements that turn out to be inconsistent with the underlying knowledge base, either on their own or in combination with each other — together with suggestions on how to resolve them.
News
- 2026 — Paper “How Cultural Background and Cognitive Style Shape Responses to Sustainability-Aware Explanations in Healthy Food Recommender Systems” has been accepted to CIKM’26.
- 2026 — Paper “When Do Contrastive Explanations Really Matter in Recommender Systems?” has been accepted to RecSys’26.
- 2025 — Multiple workshop papers accepted at IntRS’25, ConfWS 2025, and RecSoGood 2025, focusing on LLM-enhanced recommender systems and product-line engineering.
- 2024 — Paper “Less is More: Towards Sustainability-Aware Persuasive Explanations in Recommender Systems” accepted at RecSys 2024.
- 2024 — Paper “Sports Recommender Systems: Overview and Research Directions” published in the Journal of Intelligent Information Systems.
- 2023, 2024 — Nominated for the Best Teaching Award for the course Introduction to Structured Programming at TU Graz.
Featured Publications
How Cultural Background and Cognitive Style Shape Responses to Sustainability-Aware Explanations in Healthy Food Recommender Systems
Thi Ngoc Trang Tran, Viet-Man Le, Alexander Felfernig, Sebastian Lubos, Thi Minh Ngoc Chau, Li Chen, Gerhard Leitner, Mehrdad Rostami, Amir Mollazadeh
ACM International Conference on Information and Knowledge Management (CIKM 2026) — just accepted. CORE A (2026)
When Do Contrastive Explanations Really Matter in Recommender Systems?
Thi Ngoc Trang Tran, Sebastian Lubos, Alexander Felfernig, Mehrdad Rostami, Viet-Man Le, Damian Garber
ACM Conference on Recommender Systems (RecSys 2026) — just accepted. CORE A (2026)
Towards LLM-Enhanced Group Recommender Systems
Sebastian Lubos, Thi Ngoc Trang Tran, Viet-Man Le, Damian Garber, Manuel Henrich, Reinhard Willfort, Jeremias Fuchs
12th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2025), co-located with RecSys 2025. CEUR-WS, vol. 4027 (2025)
Less Is More: Towards Sustainability-Aware Persuasive Explanations in Recommender Systems
Thi Ngoc Trang Tran, Seda Polat Erdeniz, Alexander Felfernig, Sebastian Lubos, Merfat El Mansi, Viet-Man Le
18th ACM Conference on Recommender Systems. RecSys ’24. ACM, pp. 1108–1112. CORE A (2024)
LLM-generated Explanations for Recommender Systems
Sebastian Lubos, Thi Ngoc Trang Tran, Alexander Felfernig, Seda Polat Erdeniz, Viet-Man Le
Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization. UMAP ’24 Adjunct. ACM, pp. 276–285 (2024)
InformedQX: Informed Conflict Detection for Over-Constrained Problems
Viet-Man Le, Alexander Felfernig, Thi Ngoc Trang Tran, Mathias Uta
Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 9, pp. 10616–10623. CORE A* (2024)
Employing Nudge Theory and Persuasive Principles with Explainable AI in Clinical Decision Support
Seda Polat Erdeniz, Thi Ngoc Trang Tran, Alexander Felfernig, Sebastian Lubos, Michael Schrempf, Diether Kramer, Peter P. Rainer
2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2983–2989 (2023)
An Overview of Consensus Models for Group Decision-Making and Group Recommender Systems
Thi Ngoc Trang Tran, Alexander Felfernig, Viet Man Le
User Modeling and User-Adapted Interaction, vol. 34, no. 3, pp. 489–547 (2023)
Concentrating on the Impact: Consequence-based Explanations in Recommender Systems
Sebastian Lubos, Thi Ngoc Trang Tran, Seda Polat Erdeniz, Merfat El Mansi, Alexander Felfernig, Manfred Wundara, Gerhard Leitner
10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), co-located with RecSys 2023. CEUR-WS, vol. 3534 (2023)
Thi Ngoc Trang Tran, Alexander Felfernig, Viet Man Le, Thi Minh Ngoc Chau, Thu Giang Mai
Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. UMAP ’23. ACM, pp. 54–65. CORE A (2023)
FastDiagP: An Algorithm for Parallelized Direct Diagnosis
Viet-Man Le, Cristian Vidal Silva, Alexander Felfernig, David Benavides, José Galindo, Thi Ngoc Trang Tran
Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 5, pp. 6442–6449. CORE A* (2023)
Do Users Appreciate Explanations of Recommendations? An Analysis in the Movie Domain
Thi Ngoc Trang Tran, Viet Man Le, Muesluem Atas, Alexander Felfernig, Martin Stettinger, Andrei Popescu
Fifteenth ACM Conference on Recommender Systems. RecSys ’21. ACM, pp. 645–650. CORE A (2021)
Humanized Recommender Systems: State-of-the-Art and Research Issues
Thi Ngoc Trang Tran, Alexander Felfernig, Nava Tintarev
ACM Transactions on Interactive Intelligent Systems, vol. 11, no. 2, pp. 1–41 (2021)
DirectDebug: Automated Testing and Debugging of Feature Models
Viet-Man Le, Alexander Felfernig, Mathias Uta, David Benavides, José Galindo, Thi Ngoc Trang Tran
2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER), pp. 81–85. CORE A* (2021)
Recommender Systems in the Healthcare Domain: State-of-the-Art and Research Issues
Thi Ngoc Trang Tran, Alexander Felfernig, Christoph Trattner, Andreas Holzinger
Journal of Intelligent Information Systems, vol. 57, no. 1, pp. 171–201 (2020)
Towards Social Choice-Based Explanations in Group Recommender Systems
Thi Ngoc Trang Tran, Müslüm Atas, Alexander Felfernig, Viet Man Le, Ralph Samer, Martin Stettinger
Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization. UMAP ’19. ACM, pp. 13–21. CORE A (2019)
User Interfaces for Counteracting Decision Manipulation in Group Recommender Systems
Thi Ngoc Trang Tran, Alexander Felfernig, Viet Man Le, Müslüm Atas, Martin Stettinger, Ralph Samer
Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization. UMAP ’19 Adjunct. ACM, pp. 93–98 (2019)
Liquid Democracy in Group-based Configuration
Müslüm Atas, Thi Ngoc Trang Tran, Ralph Samer, Alexander Felfernig, Martin Stettinger, Davide Fucci
20th International Configuration Workshop (ConfWS 2018), CEUR-WS, vol. 2220, pp. 93–98 — Best Paper Award (2018)
Investigating Serial Position Effects in Sequential Group Decision Making
Thi Ngoc Trang Tran, Müslüm Atas, Alexander Felfernig, Ralph Samer, Martin Stettinger
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization. UMAP ’18. ACM, pp. 239–243. CORE A (2018)
Alexander Felfernig, Nava Tintarev, Thi Ngoc Trang Tran, Martin Stettinger
Group Recommender Systems: An Introduction, pp. 105–126 (2018)
An Overview of Recommender Systems in the Healthy Food Domain
Thi Ngoc Trang Tran, Müslüm Atas, Alexander Felfernig, Martin Stettinger
Journal of Intelligent Information Systems, vol. 50, no. 3, pp. 501–526 (2017)
See the selected publications for the full curated list.