Ege Kesim

Papers

Total Citations

H-Index

About

Ege Kesim is a researcher at the intersection of human–robot interaction (HRI) and multimodal data analysis, with a primary focus on understanding and measuring engagement in social robotics. Their most notable contribution is the creation of the eHRI database, a pioneering multimodal resource that captures rich behavioral data—including visual, auditory, and physiological signals—from human–robot interaction scenarios. This database, published in 2023 and already garnering 4 citations, provides a standardized benchmark for studying how people engage with robots, enabling researchers to develop more adaptive and socially aware robotic systems. By addressing the critical challenge of quantifying engagement in real-time interactions, Kesim’s work supports advances in robot perception and response generation, with implications for assistive technologies, education, and collaborative robotics. Their efforts help bridge the gap between raw sensor data and meaningful social cues, laying a foundation for more intuitive and effective human–robot partnerships. As the field of HRI grows, Kesim’s contributions to data infrastructure and engagement modeling position them as a key figure in shaping how robots understand and interact with humans.