Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval
Full Professor
Univ.-Prof. Mag. Dr. Markus Schedl
Johannes Kepler University Linz
About
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.
Research output
Publications
Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Cognitive Effects and Biases in Large Language Models
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics
Distillation-Based Layer Dropping (DLD): Effective end-to-end Framework for Dynamic Speech Networks
Proceedings of the 51st IEEE International Conference on Acoustics, Speech, and Signal Processing
Extending Logic Tensor Networks to Implicit Feedback for Representation-Aware Music Recommendation
European Conference on Information Retrieval
Face-Voice Association with Inductive Bias for Maximum Class Separation
Proceedings of the 51st IEEE International Conference on Acoustics, Speech, and Signal Processing
H-RAG at SemEval-2026 Task 8: Hierarchical Parent–Child Retrieval for Multi-Turn RAG Conversations
Proceedings of the 20th International Workshop on Semantic Evaluation
How Far Can Pretrained LLMs Go in Symbolic Music? Controlled Comparisons of Supervised and Preference-based Adaptation
Proceedings of the 4th Workshop on NLP for Music and Audio
Linking Faces and Voices Across Languages: Insights from the FAME 2026 Challenge
Proceedings of the 51st IEEE International Conference on Acoustics, Speech, and Signal Processing
Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
Adjunct Proceedings of the 34th ACM Conference on User Modeling, Adaptation and Personalization
Networked Tastes: Homophily for Music Recommendation
Workshops Proceedings of the 34th ACM International Conference on User Modeling, Adaptation and Personalization (UMAP 2026), Gothenburg, Sweden.
Read Between the Tracks: Exploring LLM-driven Intent-based Music Recommendations
Proceedings of the 4th Workshop on NLP for Music and Audio
Robust Harmful Meme Detection under Missing Modalities via Shared Representation Learning
Proceedings of the 1st Workshop on Applied AI and Multimodal Visualization Technologies
SB-BEVFusion: Enhancing the Robustness against Sensor Malfunction and Corruptions
Proceedings of the IEEE International Conference on Image Processing (ICIP)
Towards Fair ASR for Second Language Speakers using Fairness Prompted Finetuning
Proceedings of the 51st IEEE International Conference on Acoustics, Speech, and Signal Processing
AI-Generated Song Detection via Lyrics Transcripts
Proceedings of the 26th International Society for Music Information Retrieval Conference
Audio, Lyrics, Videoclips, Interactions? An Analysis of Uni- and Multi-modal Music Retrieval Systems in Terms of Accuracy and Beyond-accuracy Aspects
Proceedings of the 3rd Music Recommender Systems Workshop (MuRS) co-located with the 19th ACM Conference on Recommender Systems (RecSys 2025), Prague, Czech Republic.
Characterizing Positional Bias in Large Language Models: A Multi-Model Evaluation of Prompt Order Effects
Findings of the Association for Computational Linguistics: EMNLP 2025
Debiasing Implicit Feedback Recommenders via Sliced Wasserstein Distance-based Regularization
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Double Entendre: Robust Audio-Based AI-Generated Lyrics Detection via Multi-View Fusion
Findings of the Association for Computational Linguistics: ACL 2025
Enhancing Music Recommender Systems with Multimedia Content: A Context-Aware Approach
Proceedings of the 26th International Society for Music Information Retrieval Conference
ExIM: Exploring Intent of Music Listening for Retrieving User-generated Playlists
CHIIR'25 Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval
Familiarizing with Music: Discovery Patterns for Different Music Discovery Needs
Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization
Fine-tuning for Inference-efficient Calibrated Recommendations
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Hybrid AI for Human-Centric Personalization (HyPer)
Proceedings of the 33nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
Hybrid Personalization Using Declarative and Procedural Memory Modules of the Cognitive Architecture ACT-R
Proceedings of the 33nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
Iguanodon: A Code-Breaking Game for Improving Visualization Construction Literacy
IEEE Transactions on Visualization and Computer Graphics
Investigating Carbon Footprint of Recommender Systems Beyond Training Time
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Investigating Music Track Liking in the Halo of Album Covers
Proceedings of the 26th International Society for Music Information Retrieval Conference
Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Mitigating Gender Bias in Job Ranking Systems Using Job Advertisement Neutrality
Proceedings of the Fourth Workshop on NLP for Positive Impact (NLP4PI)
Mitigating Latent User Biases in Pre-trained VAE Recommendation Models via On-demand Input Space Transformation
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Music4All A+A: A Multimodal Dataset for Music Information Retrieval Tasks
Proceedings of the 22nd IEEE International Conference on Content-based Multimedia Indexing (CBMI 2025)
Nuanced Music Emotion Recognition via a Semi-Supervised Multi-Relational Graph Neural Network
Transactions of the International Society for Music Information Retrieval
PAEFF: Precise Alignment and Enhanced Gated Feature Fusion for Face-Voice Association
Proceedings of the Annual Conference of the International Speech Communication Association
Parameter-Efficient Single Collaborative Branch for Recommendation
Proceedings of the Nineteenth ACM Conference on Recommender Systems
Psychological Aspects in Retrieval and Recommendation
SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval
Single-Branch Network Architectures to Close the Modality Gap in Multimodal Recommendation
ACM Transactions on Recommender Systems
Why Context Matters: Exploring How Musical Context Impacts User Behavior, Mood, and Musical Preferences
Proceedings of the 33nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
Proceedings of the 18th ACM Conference on Recommender Systems (RecSys)
A Synopsis of FAME 2024 Challenge: Associating Faces with Voices in Multilingual Environments
Companion of the 32nd ACM International Conference on Multimedia (MM)
Content-driven music recommendation: Evolution, state of the art, and challenges
Computer Science Review
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters
The 18th Conference of the European Chapter of the Association for Computational Linguistics March 17-22, 2024
Emotion-Based Music Recommendation from Quality Annotations and Large-Scale User-Generated Tags
Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024)
Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024)
Award · Best Student Paper Award
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems
Proceedings of the 18th ACM Conference on Recommender Systems (RecSys)
Psychology-informed Information Access Systems Workshop
Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM 2024)
Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation (BIAS @ SIGIR 2024)
The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily
Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 18th ACM Conference on Recommender Systems (RecSys 2024)
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations
Advances in Bias and Fairness in Information Retrieval
Computational Versus Perceived Popularity Miscalibration in Recommender Systems
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
Differential Privacy in Collaborative Filtering Recommender Systems: A Review
Frontiers in Big Data - Recommender Systems
Domain Information Control at Inference Time for Acoustic Scene Classification
31st European Signal Processing Conference, (EUSIPCO) 2023, Helsinki,Finland, September 4-8, 2023
Emotion-aware Music Tower Blocks (EmoMTB): An Intelligent Audiovisual Interface for Music Discovery and Recommendation
International Journal of Multimedia Information Retrieval (IJMIR)
Exploring emotions in Bach chorales: a multi-modal perceptual and data-driven study
Royal Society Open ScienceSpringer
Exploring Intensities of Hate Speech on Social Media: A Case Study on Explaining Multilingual Models with XAI
Proceedings of the 4th Conference on Language, Data and Knowledge
Fairness of Recommender Systems in the Recruitment Domain: An Analysis from Technical and Legal Perspectives
Frontiers in Big Data - Recommender Systems
Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning
Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR 2023) co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023)
Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation
Proceedings of the 17th ACM Conference on Recommender Systems (RecSys)
Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks
Findings of the Association for Computational Linguistics: ACL 2023
Multiobjective Hyperparameter Optimization of Recommender Systems
Proceedings of the 3rd Workshop on Perspectives on the Evaluation of Recommender Systems co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, Singapore.
Music Emotions in Solo Piano: Bridging the Gap Between Human Perception and Machine Learning
Proceedings of the 16th International Symposium on Computer Music Multidisciplinary Research (CMMR 2023), .
Parameter-efficient Modularised Bias Mitigation via AdapterFusion
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
Personalized Human-Computer Interaction
Personalized Human-Computer Interaction
Personalized Human-Computer Interaction
Personalized Human-Computer Interaction
Predicting the Price of Bitcoin Using Sentiment-Enriched Time Series Forecasting
Big Data and Cognitive Computing
ReuseKNN: Neighborhood Reuse for Differentially Private KNN-Based Recommendations
ACM Transactions on Intelligent Systems and Technology
Towards Potential Applications of Machine Learning in Computer-Assisted Vocal Training
Proceedings of the 16th International Symposium on Computer Music Multidisciplinary Research (CMMR 2023), .
Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023)
Trustworthy Algorithmic Ranking Systems
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023)
Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives
Proceedings of the 17th ACM Conference on Recommender Systems
Affect in Multimedia: Benchmarking Violent Scenes Detection
IEEE Transactions on Affective Computing
An Exploratory Study on the Acoustic Musical Properties to Decrease Self-Perceived Anxiety
International Journal of Environmental Research and Public Health
EmoMTB: Emotion-aware Music Tower Blocks
Proceedings of the 2022 ACM International Conference on Multimedia Retrieval (ICMR)
Explainability in music recommender systems
AI Magazine
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization
Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), Seattle, WA, USA, 18th-23rd September
Music4All-Onion -- A Large-Scale Multi-Faceted Content-Centric Music Recommendation
Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM)
ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations
Proceedings of the 16th ACM Conference on Recommender Systems (RecSys)
Recommender Systems Handbook (3rd edition)
Recommender Systems Handbook (3rd edition)
Recommender Systems Handbook (3rd edition)
Recommender Systems Handbook (3rd edition)
Recommender Systems under European AI Regulations
Communications of the ACM
Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms
Proceedings of the 23rd International Society for Music Information Retrieval Conference, ISMIR 2022, Bengaluru, India, December 4-8
Award · Best Student Paper Award
Unlearning Protected User Attributes in Recommendations with Adversarial Training
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
Unsupervised Graph Embeddings for Session-based Recommendation with Item Features
CARS Workshop on Context-Aware Recommender Systems (RecSys)
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
Proceedings of the 15th ACM Conference on Recommender Systems (RecSys)
Automatic Recognition of Texture in Renaissance Music
International Society for Music Information Retrieval
Investigating Gender Fairness of Recommendation Algorithms in the Music Domain
Information Processing & Management
LEMONS: Listenable Explanations for Music recOmmeNder Systems
Proceedings of the 43rd European Conference on Information Retrieval (ECIR)
Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes
Frontiers in Artificial Intelligence
Psychology-Informed Recommender Systems
Foundations and Trends in Information Retrieval
Intelligent User Interfaces for Music Discovery
Transactions of the International Society for Music Information Retrieval
Modeling Popularity and Temporal Drift of Music Genre Preferences
Transactions of the International Society for Music Information Retrieval
Personality Bias of Music Recommendation Algorithms
Proceedings of the 14th ACM Conference on Recommender Systems (RecSys)
Personality Correlates of Music Audio Preferences for Modelling Music Listeners
Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
Preface to the Special Issue on User Modeling for Personalized Interaction with Music
User Modeling and User-Adapted Interaction
Recommender Systems Leveraging Multimedia Content
ACM Computing Surveys
User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues
Transactions of the International Society for Music Information Retrieval