Benedikt Loepp, M. Sc.

Benedikt received his bachelor’s (2011) and master’s degree (2013, with distinction) in Applied Computer Science at the University of Duisburg-Essen. Already while studying, he started to work as a student assistant, among others, in the Interactive Systems group. Benedikt joined the group as a researcher in March 2012. Since then, he has been administrative coordinator for Computer Science in the MINTroduce project, supporting study beginners and being responsible for the program’s preliminary courses.

In 2013, Benedikt became a full member of the Interactive Systems group. His research focuses on the field of recommender systems, in particular, preference elicitation, interactive recommending and user studies. Besides, Benedikt was involved in the ColognE-mobil project part II, where he was responsible for developing smart navigation solutions for intermodal mobility chains. He contributed to several research developments, e.g. Blended Recommending, TagMF, the Archaeological Sandbox and several GWAPs.

Benedikt also enjoys his teaching activities, including a lecture on Recommender Systems. From 2014 to 2020 he has been webmaster of the official ACM RecSys website and served as web chair for the conference. Moreover, regularly serves as a committee member and reviewer for a variety of journals and conferences. Most recently, Benedikt became one of the founding members of the GI group on User-centered AI.


Phone +49 (203) 379-3946
Fax +49 (203) 379-3557
Office LF 285
LSF view

Selected publications

On the Use of Feature-based Collaborative Explanations: An Empirical Comparison of Explanation Styles

Measuring the Impact of Recommender Systems – A Position Paper on Item Consumption in User Studies

Impact of Consuming Suggested Items on the Assessment of Recommendations in User Studies on Recommender Systems

Towards Interactive Recommending in Model-based Collaborative Filtering Systems


Interactive Recommending with Tag-Enhanced Matrix Factorization (TagMF)

Impact of Item Consumption on Assessment of Recommendations in User Studies

Recommending Running Routes: Framework and Demonstrator

Understanding Latent Factors Using a GWAP

Explaining Recommendations by Means of User Reviews

Eine Sandbox zur physisch-virtuellen Exploration von Ausgrabungsstätten

Sequential User-based Recurrent Neural Network Recommendations

Enhancing an Interactive Recommendation System with Review-based Information Filtering

All 29 publication

Main research topics

Recent teaching

Administrative and scientific functions

Review activities