Dr. Mebarka Allaoui | Machine Learning and AI Applications | Best Paper Award
Bishop’s University | Canada
Dr. Mebarka Allaoui dedicated computer science researcher with a strong background in machine learning, manifold learning, and computer vision, this scholar holds a PhD in Computer Science focused on embedding techniques and their applications to visual data analysis. Their academic journey includes a master’s degree in industrial computer science and a bachelor’s degree in information systems, all completed with high distinction. Professionally, they have served as a Postdoctoral Fellow contributing to industry-funded research on anomaly detection, developing novel embedding, deep learning, and clustering methods to enhance the interpretability of latent representations and improve fraud detection in real-world financial datasets. Prior experience includes working as a computer engineer supporting system administration, software development, data analysis, and network configuration, alongside several teaching appointments delivering practical courses in software engineering, algorithmics, and web development. Their research contributions span dimensionality reduction, clustering, optimization, document analysis, and scientific information retrieval, with publications in reputable journals and conferences. Collaborative work further extends to studies on optimizers, object detection, and embedding initialization strategies. Recognized for high-quality academic performance and impactful research outputs, they continue to advance data-driven methodologies, aiming to bridge theoretical innovation with practical applications in intelligent systems and decision-support technologies.
Profile : Google Scholar
Featured Publications
Allaoui, M., Kherfi, M. L., & Cheriet, A. (2020). “Considerably improving clustering algorithms using UMAP dimensionality reduction technique” in International Conference on Image and Signal Processing, 317–325.
Drid, K., Allaoui, M., & Kherfi, M. L. (2020). “Object detector combination for increasing accuracy and detecting more overlapping objects” in International Conference on Image and Signal Processing, 290–296.
Allaoui, M., Belhaouari, S. B., Hedjam, R., Bouanane, K., & Kherfi, M. L. (2025). “t-SNE-PSO: Optimizing t-SNE using particle swarm optimization” in Expert Systems with Applications, 269, 126398.
Allaoui, M., Kherfi, M. L., Cheriet, A., & Bouchachia, A. (2024). “Unified embedding and clustering” in Expert Systems with Applications, 238, 121923.
Allaoui, M., Kherfi, M. L., & Cheriet, A. (2020). “International Conference on Image and Signal Processing” in Springer.