Ewen MacDonald

University of Waterloo, Technical University of Denmark

Papers

Total Citations

H-Index

About

Ewen MacDonald is a researcher at the forefront of human-robot interaction, specializing in how robots can perceive and respond to human social cues. His work focuses on enabling humanoid robots to engage in natural, real-time conversations by mastering spatial awareness and non-verbal communication. A key contribution is his development of methods for robots to estimate a speaker’s direction using binaural acoustic signals, optimizing direction-of-arrival (DOA) algorithms for real-time applications—a critical step toward seamless human-robot dialogue. In his most-cited paper (2023, 4 citations), MacDonald explores how robots can adopt natural head and body orientations during conversations with moving partners, drawing on motion capture analysis of human behavior. This work addresses the challenging task of dynamic social positioning, ensuring robots maintain appropriate engagement without appearing rigid. His earlier research on playful interaction with voice-sensing modular robots (2013, 3 citations) further demonstrates his commitment to making robotic systems intuitive and responsive. Though his citation counts are modest, MacDonald’s contributions are foundational for the next generation of socially aware robots, bridging the gap between human conversational norms and robotic execution. His work is essential reading for students and researchers interested in embodied AI, social robotics, and acoustic sensing.