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About

Irina Mocanu is a leading researcher at the intersection of computer vision, social robotics, and assistive technologies. Her most impactful work, the highly cited "Comprehensive Survey of Indoor Localization Methods Based on Computer Vision" (176 citations), establishes her as a key authority in vision-based tracking and localization. She has made significant contributions to human-robot interaction through the development of the AMIRO Social Robotics Framework, deployed and evaluated on the Pepper robot, which addresses the growing demand for affordable, focused social robotics platforms in retail, entertainment, and active and assisted living (AAL). Mocanu’s research extends to human activity recognition using convolutional neural networks on the TIAGo robot, combining spatial and temporal data for robust scene understanding. She has also developed intuitive solutions for elderly care, automatic data collection, and safe object manipulation for assistive robots, including automatic grasping point identification. Her work on using the TIAGo robot to facilitate learning and improve education further demonstrates her commitment to real-world applications. With a portfolio spanning foundational surveys to practical robotic deployments, Mocanu’s research is driving the future of intelligent, human-centered robotics.