Latifa Oukhellou

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About

Latifa Oukhellou is a leading researcher whose work bridges the fields of artificial intelligence, assistive robotics, and information fusion. Her primary research areas include belief function theory, machine learning, and human-robot interaction, with a particular focus on developing intelligent systems for healthcare and telecommunications. Oukhellou’s notable contribution, "Belief functions in telecommunications and network technologies: an overview" (2014, 10 citations), provides a foundational synthesis of how evidential reasoning can enhance decision-making in complex network environments. More recently, she has advanced the frontier of assistive robotics through her work on online human intention detection, as demonstrated in her 2022 paper (2 citations). This research proposes a machine-learning-based framework that enables seamless control of lower-limb wearable robots, such as actuated-ankle-foot orthoses, by accurately predicting user intent in real time. Her work directly addresses the critical challenge of smooth human-robot interaction, with profound implications for rehabilitation and mobility assistance. Oukhellou’s interdisciplinary approach—combining theoretical models with practical, task-oriented control—positions her as a key contributor to the development of smarter, more responsive assistive technologies.