Muhammet Furkan Ilaslan
Papers
1
Total Citations
6
H-Index
1
About
Muhammet Furkan Ilaslan is a researcher at the forefront of human-robot interaction and multimodal AI, with a focus on understanding human intention through video and eye-gaze analysis. His key research areas include egocentric vision, video question answering (VQA), and task-oriented collaboration. Ilaslan’s major contribution is the development of GazeVQA, a novel dataset that integrates exocentric and egocentric video with eye-gaze information to enable machines to interpret human actions during collaborative tasks. This work, published in 2023, has already garnered 6 citations, signaling its growing influence in the field. By leveraging gaze as a critical cue, Ilaslan’s research bridges the gap between computer vision and robotics, paving the way for more intuitive human-robot teamwork. His innovative approach to VQA—using multiview perspectives—stands out as a pioneering effort in a nascent area, offering a foundation for future studies in intention-aware AI. Ilaslan’s work not only advances academic understanding but also holds practical promise for applications in assistive robotics and collaborative systems, making him a rising voice in the intersection of vision, language, and interaction.
Research Focus
Key Achievements
Top Papers
- 1