Panagiotis Papapetrou

Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science, Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS), he contributes to shaping AI research directions in Sweden.

• Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics
• Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization
• Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021)

His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction.

Recent scientific contributions include:

• CounterFair (2024): Group fairness analysis via counterfactual burden metrics
• M-ClustEHR (2024): Multimodal clustering for electronic health records
• COMET (2024): Constraint-based glucose forecasting explanations
• Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition
• Z-Time (2024): Interpretable multivariate time series classification

His editorial leadership includes:

• Action Editor at Machine Learning Journal (since 2024)
• Action Editor at Data Mining and Knowledge Discovery (since 2018)
• Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)