Benedikt Loepp

I am an assistant professor (Juniorprofessor) for computational social science and data science at the University of Koblenz. My background lies in the intersection of human-computer interaction and machine learning, with a particular interest in recommender systems, especially interactive approaches, user modeling, and preference elicitation. In my current work, I am focusing on exploring digital human behavior and personal characteristics within data-intensive real-world systems to understand and improve the adoption of these systems based on user-centric insights, as well as on creating accessible AI-based decision-making tools to address societal challenges but also support individuals in their daily lives by incorporating interventions based on mixed-methods user experience research.

I received a bachelor’s degree (2011) and a master’s degree (2013) in Applied Computer Science as well as a PhD in Computer Science (Dr.-Ing.) from the University of Duisburg-Essen. From 2012 to 2023, I worked there as a doctoral researcher and as a postdoc in the Interactive Systems group. From 2012 to 2020, I was also the coordinator for computer science in the MINTroduce project at the University of Duisburg-Essen, in which I supported first-year students and was responsible for the department's preliminary courses. Moreover, I was involved in the colognE-mobil project part II and contributed to several research developments, e.g., the concept of blended recommending, the TagMF framework, the archaeological sandbox, and several GWAPs. In addition to research, I enjoyed my teaching activities, including a course on recommender systems.

For many years, I was the webmaster of the official ACM RecSys website, serving as web chair for the conference until 2020. For RecSys, I was also active as student volunteer chair and proceedings chair, and as publicity chair for ACM UMAP in 2021. I regularly serve as a committee member and reviewer for a variety of journals and conferences, including CHI, Frontiers AI, IJHCS, INTERACT, IUI, RecSys, and UMAP. I was a member of the Global Young Faculty VII and co-founded the GI group on User-centered AI.

Please also visit my page at the University of Koblenz.  

Contact

• Mail: loe(anti-spam)pp [at] un(anti-spam)i-koblenz [dot] d(anti-spam)e
• Mastodon: @BenediktLoepp@nrw.social
• Twitter: @BenediktLoepp
• LinkedIn: Benedikt Loepp

Publications

2023

• Loepp, B., & Ziegler, J. (2023).
  How Users Ride the Carousel: Exploring the Design of Multi-List Recommender Interfaces From a User Perspective.
  In RecSys '23: Proceedings of the 17th ACM Conference on Recommender Systems (pp. 1090–1095). New York, NY, USA: ACM.
   
• Loepp, B. (2023).
  Multi-List Interfaces for Recommender Systems: Survey and Future Directions.
  Frontiers in Big Data, 6.
   
• Ziegler, J., & Loepp, B. (2023).
  User-Centered Recommender Systems.
  In Augstein, M., Herder, E., & Wörndl, W. (Eds.), Personalized Human-Computer Interaction (pp. 33–58). Berlin, Germany: De Gruyter Oldenbourg.
   

2022

• Loepp, B. (2022).
  Recommender Systems Alone Are Not Everything: Towards a Broader Perspective in the Evaluation of Recommender Systems.
  In PERSPECTIVES '22: Proceedings of the 2nd Workshop on Perspectives on the Evaluation of Recommender Systems.
   
• Kleemann, T., Loepp, B., & Ziegler, J. (2022).
  Towards Multi-Method Support for Product Search and Recommending.
  In UMAP '22: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 74–79). New York, NY, USA: ACM.
   
• Buschek, D., Hauptmann, H., Heuer, H., Loepp, B., Riener, A., & Yigitbas, E. (2022).
  Workshop on User-Centered Artificial Intelligence (UCAI '22).
  In Mensch & Computer 2022 – Workshopband. Gesellschaft für Informatik.
   

2021

• Loepp, B. (2021).
  Interactive Methods for Model-based Collaborative Filtering Recommender Systems.
  University of Duisburg-Essen, Duisburg, Germany.
   
• Kleemann, T., Wagner, M., Loepp, B., & Ziegler, J. (2021).
  Modeling User Interaction at the Convergence of Filtering Mechanisms, Recommender Algorithms and Advisory Components.
  In Mensch & Computer 2021 – Tagungsband (pp. 531–543). New York, NY, USA: ACM.
   
• Loepp, B. (2021).
  On the Convergence of Intelligent Decision Aids.
  In UCAI '21: Proceedings of the 2nd Workshop on User-Centered Artificial Intelligence. Gesellschaft für Informatik.
   
• Buschek, D., Hauptmann, H., Loepp, B., & Wörndl, W. (2021).
  Workshop on User-Centered Artificial Intelligence (UCAI '21).
  In Mensch & Computer 2021 – Workshopband. Gesellschaft für Informatik.
   

2020

• Naveed, S., Loepp, B., & Ziegler, J. (2020).
  On the Use of Feature-based Collaborative Explanations: An Empirical Comparison of Explanation Styles.
  In ExUM '20: Proceedings of the International Workshop on Transparent Personalization Methods based on Heterogeneous Personal Data (pp. 226–232). New York, NY, USA: ACM.
   
• Augstein, M., Buschek, D., Herder, E., Loepp, B., Yigitbas, E., & Ziegler, J. (2020).
  Workshop on User-Centered Artificial Intelligence (UCAI '20).
  In Mensch & Computer 2020 – Workshopband. Gesellschaft für Informatik.
   
• Buschek, D., Loepp, B., & Ziegler, J. (2020).
  Editorial of the i-com Special Issue on User-Centered Artificial Intelligence.
  i-com, 19(3), 169.
   
• Ziegler, J., & Loepp, B. (2020).
  Empfehlungssysteme.
  In Kollmann, T. (Ed.), Handbuch Digitale Wirtschaft (pp. 717–741). Wiesbaden, Germany: Springer Gabler.
   

2019

• Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2019).
  Interactive Recommending with Tag-Enhanced Matrix Factorization (TagMF).
  International Journal of Human-Computer Studies, 121, 21–41.
   
• Loepp, B., & Ziegler, J. (2019).
  Towards Interactive Recommending in Model-based Collaborative Filtering Systems.
  In RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems (pp. 546–547). New York, NY, USA: ACM.
   
• Loepp, B., & Ziegler, J. (2019).
  Measuring the Impact of Recommender Systems – A Position Paper on Item Consumption in User Studies.
  In Impact RS '19: Proceedings of the 1st Workshop on Impact of Recommender Systems.
   
• Kunkel, J., Loepp, B., Dolff, E., & Ziegler, J. (2019).
  LittleMissFits: Ein Game-With-A-Purpose zur Evaluierung subjektiver Verständlichkeit von latenten Faktoren in Empfehlungssystemen.
  In Gam-R '19: Proceedings of the Mensch & Computer 2019 Workshop Gam-R – Gamification Reloaded. Gesellschaft für Informatik e.V.
   
• Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2019).
   invited to the sister conference best paper track 
  Impact of Consuming Suggested Items on the Assessment of Recommendations in User Studies on Recommender Systems.
  In IJCAI '19: Proceedings of the 28th International Joint Conference on Artificial Intelligence (pp. 6201–6205). IJCAI Organization.
   

2018

• Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2018).  best short paper 
  Impact of Item Consumption on Assessment of Recommendations in User Studies.
  In RecSys '18: Proceedings of the 12th ACM Conference on Recommender Systems (pp. 49–53). New York, NY, USA: ACM.
   
• Kunkel, J., Loepp, B., & Ziegler, J. (2018).
  Understanding Latent Factors Using a GWAP.
  In LBRS@RecSys '18: Proceedings of the Late-Breaking Results track part of the 12th ACM Conference on Recommender Systems.
   
• Kunkel, J., Loepp, B., & Ziegler, J. (2018).
  Ein Online-Spiel zur Benennung latenter Faktoren in Empfehlungssystemen.
  In Mensch & Computer 2018 – Tagungsband. Gesellschaft für Informatik.
   
• Donkers, T., Loepp, B., & Ziegler, J. (2018).
  Explaining Recommendations by Means of User Reviews.
  In ExSS '18: Proceedings of the 1st Workshop on Explainable Smart Systems.
   
• Loepp, B., & Ziegler, J. (2018).
  Recommending Running Routes: Framework and Demonstrator.
  In ComplexRec '18: Proceedings of the 2nd Workshop on Recommendation in Complex Scenarios (pp. 26–29).
   

2017

• Kunkel, J., Loepp, B., & Ziegler, J. (2017).
  A 3D Item Space Visualization for Presenting and Manipulating User Preferences in Collaborative Filtering.
  In IUI '17: Proceedings of the 22nd International Conference on Intelligent User Interfaces (pp. 3–15). New York, NY, USA: ACM.
   
• Donkers, T., Loepp, B., & Ziegler, J. (2017).
  Sequential User-Based Recurrent Neural Network Recommendations.
  In RecSys '17: Proceedings of the 11th ACM Conference on Recommender Systems (pp. 152–160). New York, NY, USA: ACM.
   
• Feuerbach, J., Loepp, B., Barbu, C.-M., & Ziegler, J. (2017).
  Enhancing an Interactive Recommendation System with Review-based Information Filtering.
  In IntRS '17: Proceedings of the 4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (pp. 2–9).
   
• Biefang, K., Kunkel, J., Loepp, B., & Ziegler, J. (2017).  best demo 
  Eine Sandbox zur physisch-virtuellen Exploration von Ausgrabungsstätten.
  In Mensch & Computer 2017 – Workshopband. Gesellschaft für Informatik.
   
• Loepp, B., & Ziegler, J. (2017).
  Empirische Bedarfsanalyse zur intermodalen Navigation und dem Einsatz von Informationssystemen zur Förderung ihrer Attraktivität.
  In Proff, H. & Fojcik, T. M. (Eds.), Innovative Produkte und Dienstleistungen in der Mobilität: Technische und betriebswirtschaftliche Aspekte (pp. 409–426). Wiesbaden, Germany: Springer Gabler.
   
• Loepp, B., & Ziegler, J. (2017).
  On User Awareness in Model-Based Collaborative Filtering Systems.
  In AWARE '17: Proceedings of the 1st Workshop on Awareness Interfaces and Interactions.
   

2016

• Donkers, T., Loepp, B., & Ziegler, J. (2016).
  Tag-Enhanced Collaborative Filtering for Increasing Transparency and Interactive Control.
  In UMAP '16: Proceedings of the 24th ACM International Conference on User Modeling, Adaptation and Personalization (pp. 169–173). New York, NY, USA: ACM.
   
• Loepp, B., Barbu, C.-M., & Ziegler, J. (2016).
  Interactive Recommending: Framework, State of Research and Future Challenges.
  In EnCHIReS '16: Proceedings of the 1st Workshop on Engineering Computer-Human Interaction in Recommender Systems (pp. 3–13).
   
• Donkers, T., Loepp, B., & Ziegler, J. (2016).
  Towards Understanding Latent Factors and User Profiles by Enhancing Matrix Factorization with Tags.
  In RecSys '16: Poster Proceedings of the 10th ACM Conference on Recommender Systems.
   

2015

• Loepp, B., Herrmanny, K., & Ziegler, J. (2015).
  Blended Recommending: Integrating Interactive Information Filtering and Algorithmic Recommender Techniques.
  In CHI '15: Proceedings of the 33rd ACM International Conference on Human Factors in Computing Systems (pp. 975–984). New York, NY, USA: ACM.
   
• Loepp, B., Herrmanny, K., & Ziegler, J. (2015).
  Merging Interactive Information Filtering and Recommender Algorithms – Model and Concept Demonstrator.
  i-com, 14(1), 5–17.
   
• Donkers, T., Loepp, B., & Ziegler, J. (2015).
  Merging Latent Factors and Tags to Increase Interactive Control of Recommendations.
  In RecSys '15: Poster Proceedings of the 9th ACM Conference on Recommender Systems.
   
• Kunkel, J., Loepp, B., & Ziegler, J. (2015).  honorable mention 
  3D-Visualisierung zur Eingabe von Präferenzen in Empfehlungssystemen.
  In Mensch & Computer 2015: Gemeinsam – Arbeit – Erleben (pp. 123–132). Berlin, Germany: De Gruyter Oldenbourg.
   

2014

• Loepp, B., Hussein, T., & Ziegler, J. (2014).  honorable mention 
  Choice-Based Preference Elicitation for Collaborative Filtering Recommender Systems.
  In CHI '14: Proceedings of the 32nd ACM International Conference on Human Factors in Computing Systems (pp. 3085–3094). New York, NY, USA: ACM.
   
• Herrmanny, K., Schering, S., Berger, R., Loepp, B., Günter, T., Hussein, T., & Ziegler, J. (2014).
  MyMovieMixer: Ein hybrider Recommender mit visuellem Bedienkonzept.
  In Mensch & Computer 2014: Interaktiv unterwegs – Freiräume gestalten (pp. 45–54). Berlin, Germany: De Gruyter Oldenbourg.
   
• Loepp, B. & Ziegler, J. (2014).
  Komplexe Präferenzprofile für intermodale Navigation.
  In Proceedings of the 3rd Workshop on Automotive HMI (pp. 191–198). Berlin, Germany: De Gruyter Oldenbourg.
   

2013

• Loepp, B., Hussein, T., & Ziegler, J. (2013).
  Interaktive Empfehlungsgenerierung mit Hilfe latenter Produktfaktoren.
  In Mensch & Computer 2013: Interaktive Vielfalt (pp. 17–26). München, Germany: Oldenbourg Verlag.
   

A list of publications is also available in the digital library of the University of Duisburg-Essen, via ORCID (iD: 0000-0001-9059-5324), or in my Google Scholar profile.