Markus Schedl

Markus Schedl

I am a Full Professor at Johannes Kepler University (JKU) Linz, Austria, affiliated with the Institute of Computational Perception, where I lead the Multimedia Mining and Search (MMS) group. In addition, I am head of the Human-centered Artificial Intelligence (HCAI) group at the Linz Institute of Technology (LIT) AI Lab. My areas of expertise include recommender systems, user modeling, information retrieval, machine learning, natural language processing, multimedia, data analysis, and web mining.

I graduated in Computer Science from the Vienna University of Technology (TU Wien) and earned my PhD degree from JKU Linz. In addition, I studied International Business Administration at the Vienna University of Economics and Business (WU Wien) and the University of Gothenburg (School of Business, Economics and Law), which led to a Master’s degree.

I have been leading and co-leading projects funded by the Austrian Science Fund (FWF), the Austrian Research Promotion Agency (FFG), and the European Commission (EC). I also maintain collaborations with industry, for instance with Siemens, Spotify, and Deezer. Furthermore, I serve as consultant on the topics mentioned above.

I am also a passionate teacher and regularly give courses at JKU (Introduction to Machine Learning, Multimedia Search and Retrieval, Learning from User-generated Data, Multimedia Data Mining, and Social Media Mining and Analysis). In addition, I spent several guest lecturing stays among others at Universitat Pompeu Fabra Barcelona, Queen Mary University of London, and Kungliga Tekniska Högskolan Stockholm.


Peer-Reviewed Journal and Conference Papers

UnlearningAdversarial screenshot

Christian Ganhör, David Penz, Navid Rekab-saz, Oleg Lesota, Markus Schedl
Unlearning Protected User Attributes in Recommendations with Adversarial Training
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022

TextureRecognition screenshot

Emilia Parada-Cabaleiro, Maximilian Schmitt , Anton Batliner , Björn Schuller , Markus Schedl
Automatic Recognition of Texture in Renaissance Music
International Society for Music Information Retrieval, 2021

LEMONS screenshot

Alessandro B. Melchiorre, Verena Haunschmid , Markus Schedl, Gerhard Widmer
LEMONS: Listenable Explanations for Music recOmmeNder Systems
European Conference on Information Retrieval, 2021

DeepGenIR screenshot

Oleg Lesota, Navid Rekab-saz, Daniel Cohen , Klaus Antonius Grasserbauer , Carsten Eickhoff , Markus Schedl
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval, 2021

Book Chapters

Markus Schedl, Knees, Peter, McFee, Brian, Bogdanov, Dmitry
Editors: Francesco Ricci, Lior Rokach, Bracha Shapira
Chapter: Music Recommendation Systems: Techniques, Use Cases, and Challenges
Recommender Systems Handbook (3rd edition)
Springer, 2022.

Deldjoo, Yashar, Markus Schedl, Hidasi, Balazs, Wei, Yinwei, He, Xiangnan
Editors: Francesco Ricci, Lior Rokach, Bracha Shapira
Chapter: Multimedia Recommender Systems: Algorithms and Challenges
Recommender Systems Handbook (3rd edition)
Springer, 2022.