Ziya Tsoy
Papers
1
Total Citations
3
H-Index
1
About
Dr. Ziya Tsoy is a leading researcher in human-robot interaction and embodied AI, with a primary focus on advancing pose estimation for humanoid robots in extended reality (XR) environments. Their most notable contribution is the development of a novel dataset and methodology for diverse humanoid robot pose estimation from images, published in 2024, which tackles the critical challenge of accurate pose detection using only sparse datasets. This work has already garnered 3 citations, signaling its growing impact in the field. Dr. Tsoy’s research bridges a key gap in robotics and computer vision, enabling more natural and responsive human-robot collaboration by allowing robots to interpret and mimic human poses with limited training data. Their approach is particularly significant for XR applications, where precise pose estimation is essential for immersive interaction. By addressing the scarcity of large-scale pose datasets for diverse humanoid robots, Dr. Tsoy has laid a foundational framework that promises to accelerate progress in autonomous systems and interactive robotics. Their work stands out for its practical relevance and potential to transform how robots perceive and engage with humans in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1