Papers

16

Total Citations

227

H-Index

8

About

Fakheredine Keyrouz is a prominent researcher specializing in binaural sound localization, robotic auditory systems, and human-inspired hearing technologies. His work sits at the intersection of signal processing, robotics, and computational auditory science, with a particular focus on enabling machines to replicate the remarkable spatial hearing capabilities of the human auditory system. Keyrouz's most significant contributions center on developing advanced algorithms for three-dimensional sound source localization using Head-Related Transfer Functions (HRTFs). His 2014 paper on binaural sound localization for humanoid robots has garnered 54 citations, while his foundational 2006 work introducing a novel HRTF-based localization method has accumulated 50 citations, reflecting the enduring influence of his early methodological innovations. He has also made meaningful advances in concurrent sound source separation, Kalman filter-based sound tracking, and binaural range estimation — extending robotic hearing systems to increasingly complex real-world scenarios. Beyond pure localization, Keyrouz has explored applications in surveillance systems and biologically inspired neural networks, broadening the practical reach of his research. His sustained body of work across humanoid robotics and spatial audio processing has established him as a key contributor to the field, providing foundational tools that continue to inform researchers designing intelligent, hearing-capable robotic systems.

Research Focus

Key Achievements

8
H-Index
16
Papers
227
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Advanced Binaural Sound Localization in 3-D for Humanoid Robots
54 citations · 2014
📈 Most Prolific Year: 2007 (8 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Notre Dame University – Louaize, Technical University of Munich, Klinikum rechts der Isar

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago