Members
Ernesto William De Luca
He is an interdisciplinary researcher with expertise in computer science, computational linguistics, information retrieval, machine learning, and digital humanities. Currently, they serve as the Head of the Digital Information and Research Infrastructures department at the Georg Eckert Institute (since 2015) and hold a professorship in digital transformation and digital humanities at Otto von Guericke University Magdeburg (since 2019). Additionally, he is an associate professor at Guglielmo Marconi University of Rome. His academic journey includes studying computational linguistics at Bielefeld University and completing a PhD in computer science at Otto von Guericke University with a focus on multilingual text retrieval. They have held various academic positions, including head of the Information Retrieval and Machine Learning competence center at the DAI-Lab of Berlin University of Technology, and previously served as a professor of information science at Potsdam University of Applied Sciences.
Julian Marvin Joers
Julian is a PhD student at the Otto Von Guericke University, Magdeburg, Germany under the supervision of Prof. Ernesto William De Luca since May 2022. The focus of Joers' research is the conceptualization, implementation, and measurement of eudaimonic interaction design, i.e. the development of user interfaces that take into account the multi-dimensional concept of eudaimonic well-being. Joers has already published studies regarding his research and plans to complete the conceptualization of eudaimonic interaction design (EID) in the summer of 2025.
Elham Motamedi
Elham is a PhD graduate from the University of Primorska, supervised by Prof. Marko Tkalčič. She is currently a research assistant at the Department for Artificial Intelligence at Jožef Stefan Institute. Her PhD research was focused on leveraging psychology-informed features, particularly eudaimonic and hedonic qualities, into recommendation systems to enhance their interpretability. Additionally, her work includes leveraging machine learning techniques to predict these features that could further enhance the effectiveness of recommendation systems.
Marko Tkalčič
Marko is a full professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He aims at improving personalized services (e.g. recommender systems) through the usage of psychological models in personalization algorithms. To achieve this, he uses diverse research methodologies, including data mining, machine learning, and user studies. Marko is a member of the IUI and UMAP community, having published, and organized workshops, being part of the organizing committee, and being a senior PC member of the conference. Marko is also involved in the UMAP and RecSys community. From the HUMANIZE workshop series (ACM IUI 2017-2024) he co-edited a book with selected chapters based on the workshop series in the Springer HCI Series.
