Papers
16
Total Citations
215
H-Index
9
About
Karim Youssef is a robotics and artificial intelligence researcher whose work spans two interconnected domains: robotic audition and social robotics. His early career focused on the challenging problem of binaural sound source localization, where he developed innovative learning-based approaches enabling robots to identify and track speakers in noisy, reverberant environments using human-like ear configurations. These foundational contributions — including methods for simultaneous speaker identification and localization — earned him recognition in the robotic audition community and remain influential, with key papers accumulating dozens of citations. Over time, Youssef broadened his scope toward social robotics, authoring a widely cited 2022 survey (48 citations) that maps the field's rapid evolution across education, medicine, and human-computer interaction. His practical work includes designing conversational reception robots and experimenting with animatronic platforms integrated with ChatGPT, demonstrating a commitment to bridging theoretical research and real-world deployment. His 2023 review of telepresence technologies further reflects his interest in how robots mediate human presence across distances. Collectively, Youssef's research trajectory illustrates a researcher who has grown from solving precise acoustic engineering problems to tackling broader questions about how robots can meaningfully integrate into human social environments.
Research Focus
Key Achievements
Top Papers
- 1A Survey on Recent Advances in Social Robotics48 citations · 2022
- 2A learning-based approach to robust binaural sound localization37 citations · 2013
- 3A binaural sound source localization method using auditive cues and vision28 citations · 2012
- 4Towards a systematic study of binaural cues14 citations · 2012
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- 8From monaural to binaural speaker recognition for humanoid robots11 citations · 2010
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