The Lab is co-supervising four Industrial Engineering master’s students, each exploring different aspects of recommender systems. Their research focuses on areas such as multi-objective optimization, bias mitigation, user intent modeling, and deep learning-based recommendation techniques. Through this collaboration, the Lab aims to advance both theoretical insights and practical applications, contributing to the development of more efficient, fair, and personalized recommendation systems.
