Yasmina Becis

Université d'Orléans, Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique

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About

Yasmina Becis is a leading researcher in assistive robotics and multi-sensor data fusion, with a primary focus on enhancing autonomy and safety for elderly populations through smart home technologies. Her most impactful work, "Indoor human/robot localization using robust multi-modal data fusion" (16 citations), pioneers the integration of diverse sensor inputs to monitor Activities of Daily Living (ADL) in retirement homes, enabling real-time assessment of elderly individuals' functional capabilities. This research directly addresses the critical challenge of aging-in-place by creating intelligent environments that can detect anomalies and support independent living. Becis further advances the field with her work on "Robust Fault Detection and Isolation applied to Indoor Localization" (4 citations), where she develops a passive, set-membership approach using interval constraint propagation to identify system faults in nonlinear localization systems. Her contributions are notable for bridging theoretical robustness with practical deployment in care facilities, ensuring that sensor failures do not compromise user safety. By combining rigorous mathematical methods with human-centered application, Becis has established herself as a key figure in the intersection of robotics, fault-tolerant systems, and gerontechnology.