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Research

Interests

  • Fair machine learning and AI
  • Student performance prediction

Supervision

  • Chunyang Fan, 6-month intern (2023)

Publication

Peer-reviewed journal papers

Peer-reviewed conference papers

  • 2023: [long paper] Mélina Verger, Sébastien Lallé, François Bouchet, Vanda Luengo. Is Your Model "MADD"? A Novel Metric to Evaluate Algorithmic Fairness for Predictive Student Models. Sixteenth International Conference on Educational Data Mining (EDM 2023), July 2023, Bangalore, India.

  • 2023: [long paper] Mélina Verger, François Bouchet, Sébastien Lallé, Vanda Luengo. Caractérisation et mesure des comportements discriminants des modèles prédictifs. 11ème Conférence sur les Environnements Informatiques pour l'Apprentissage Humain (EIAH 2023), June 2023, Brest, France. hal-04131676

  • 2022: [long paper] Mélina Verger. Investiguer la notion d'équité algorithmique dans les environnements informatiques pour l'apprentissage humain. 9ièmes RJC EIAH 2022 : Environnements Informatiques pour l’Apprentissage Humain, May 2022, Lille, France. hal-03678739

Peer-reviewed workshop papers

  • 2023: [long paper] Mélina Verger, Chunyang Fan, Sébastien Lallé, François Bouchet, Vanda Luengo. A Fair Post-Processing Method based on the MADD Metric for Predictive Student Models. 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education (RKDE 2023) at ECML PKDD 2023, September 2023, Turino, Italy.

Communication

  • 2022: [poster] NewInML at NeurIPS 2022, December 2022, Paris, France.
  • 2021: [report] Mélina Verger, Hugo Jair Escalante. Predicting students’ performance in online courses using multiple data sources. DOI: 10.48550/arXiv.2109.07903. The code and a Codalab challenge are available.