Frosina Stojanovska
Papers
2
Total Citations
9
H-Index
2
About
Frosina Stojanovska is a researcher at the intersection of computer vision, natural language processing, and human-robot interaction. Her work focuses on enabling machines to not only understand visual scenes but also to respond to human emotional states. In her most-cited paper, "Explorations into Deep Learning Text Architectures for Dense Image Captioning" (2020, 6 citations), she investigates advanced neural architectures to generate detailed, context-rich descriptions of images—a critical task for applications in assistive technologies, robotics, and automated storytelling. This contribution addresses the challenge of bridging visual perception and language generation. Additionally, Stojanovska explores affective computing in "Emotion-Aware Teaching Robot: Learning to Adjust to User’s Emotional State" (2018, 3 citations), where she develops robotic systems capable of recognizing and adapting to a user’s emotions during educational interactions. This work highlights her commitment to creating more intuitive and responsive human-machine interfaces. Though early in her career, her research lays important groundwork for empathetic, context-aware AI systems that can perceive, describe, and emotionally engage with the world.
Research Focus
Key Achievements
Top Papers
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- 2