Toward an Automatic Assistance Framework for the Selection and Configuration of Machine Learning Based Data Analytics Solutions in Industry 4.0. - Moncef Garouani; Mohamed Hamlich; Adeel Ahmad 001; Mourad Bouneffa; Grégory Bourguin; Arnaud Lewandowski (BDIoT, 2021)

Towards the Automation of Industrial Data Science: A Meta-learning based Approach. - Moncef Garouani; Adeel Ahmad 001; Mourad Bouneffa; Arnaud Lewandowski; Grégory Bourguin; Mohamed Hamlich (ICEIS (1), 2021)

Scalable Meta-Bayesian Based Hyperparameters Optimization for Machine Learning. - Moncef Garouani; Adeel Ahmad 001; Mourad Bouneffa; Mohamed Hamlich (SADASC, 2022)

Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data. - Moncef Garouani; Adeel Ahmad 001; Mourad Bouneffa; Mohamed Hamlich; Grégory Bourguin; Arnaud Lewandowski (J. Big Data, 2022)

AMLBID: An auto-explained Automated Machine Learning tool for Big Industrial Data. - Moncef Garouani; Adeel Ahmad 001; Mourad Bouneffa; Mohamed Hamlich (SoftwareX, 2022)

Towards Efficient and Explainable Automated Machine Learning Pipelines Design : Application to Industry 4.0 Data. (Vers une automatisation efficace et explicable des processus d'apprentissage automatique : Application à l'Industrie 4.0). - Moncef Garouani (2022)

Automated Decision Support Framework for IoT: Towards a Cyber Physical Recommendation System. - Mohammad Choaib; Moncef Garouani; Mourad Bouneffa; Nicolas Waldhoff; Adeel Ahmad 001; Yasser Mohanna (ICEIS (1), 2023)

Explaining Meta-Features Importance in Meta-Learning Through Shapley Values. - Moncef Garouani; Adeel Ahmad 001; Mourad Bouneffa (ICEIS (1), 2023)

Unlocking the Black Box: Towards Interactive Explainable Automated Machine Learning. - Moncef Garouani; Mourad Bouneffa (IDEAL, 2023)

Version [2.0]- [AMLBID: An auto-explained Automated Machine Learning tool for Big Industrial Data]. - Moncef Garouani; Mourad Bouneffa; Adeel Ahmad 001; Mohamed Hamlich (SoftwareX, 2023)

Autoencoder-kNN meta-model based data characterization approach for an automated selection of AI algorithms. - Moncef Garouani; Adeel Ahmad 001; Mourad Bouneffa; Mohamed Hamlich (J. Big Data, 2023)

IoT Sensor Selection in Cyber-Physical Systems: Leveraging Large Language Models as Recommender Systems. - Mohammad Choaib; Moncef Garouani; Mourad Bouneffa; Yasser Mohanna (CoDIT, 2024)

Prédictibilité de la prédiction de la performance des requêtes ? Une approche basée sur les valeurs aberrantes multivariées. - Adrian-Gabriel Chifu; Sébastien Déjean; Moncef Garouani; Josiane Mothe; Diégo Ortiz; Md. Zia Ullah (CORIA, 2024)

Can We Predict QPP? An Approach Based on Multivariate Outliers. - Adrian-Gabriel Chifu; Sébastien Déjean; Moncef Garouani; Josiane Mothe; Diégo Ortiz; Md. Zia Ullah (ECIR (3), 2024)

Investigating the Duality of Interpretability and Explainability in Machine Learning. - Moncef Garouani; Josiane Mothe; Ayah Barhrhouj; Julien Aligon (ICTAI, 2024)

Model Lake : A New Alternative for Machine Learning Models Management and Governance. - Moncef Garouani; Franck Ravat; Nathalie Vallès-Parlangeau (WISE (4), 2024)

IoT-AID: An Automated Decision Support Framework for IoT. - Mohammad Choaib; Moncef Garouani; Mourad Bouneffa; Nicolas Waldhoff; Yasser Mohanna (SN Comput. Sci., 2024)

IoT-AID: Leveraging XAI for Conversational Recommendations in Cyber-Physical Systems. - Mohammad Choaib; Moncef Garouani; Mourad Bouneffa; Adeel Ahmad 001 (ICEIS (1), 2025)

Dense Retrieval for Low Resource languages - the Case of Amharic Language. - Tilahun Yeshambel; Moncef Garouani; Serge Molina; Josiane Mothe (SIGIR, 2025)

XStacking : An effective and inherently explainable framework for stacked ensemble learning. - Moncef Garouani; Ayah Barhrhouj; Olivier Teste (Inf. Fusion, 2025)

Uncovering the Limitations of Query Performance Prediction: Failures, Insights, and Implications for Selective Query Processing. - Adrian-Gabriel Chifu; Sébastien Déjean; Josiane Mothe; Moncef Garouani; Diégo Ortiz; Md. Zia Ullah (CoRR, 2025)

An experimental survey and Perspective View on Meta-Learning for Automated Algorithms Selection and Parametrization. - Moncef Garouani (CoRR, 2025)

GeMix: Conditional GAN-Based Mixup for Improved Medical Image Augmentation. - Hugo Carlesso; Maria Eliza Patulea; Moncef Garouani; Radu Tudor Ionescu; Josiane Mothe (CoRR, 2025)

XStacking: Explanation-Guided Stacked Ensemble Learning. - Moncef Garouani; Ayah Barhrhouj; Olivier Teste (CoRR, 2025)