Elie Khoury

Papers

Total Citations

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About

Elie Khoury is a leading researcher at the intersection of audio forensics and augmented reality, whose work spans deepfake detection and human-machine collaborative mapping. His most influential contribution, "Investigating voiced and unvoiced regions of speech for audio deepfake detection" (2025, 8 citations), breaks new ground by introducing interpretability into deep neural network-based anti-spoofing systems. Rather than treating detection as a black box, Khoury's work analyzes how different speech regions—voiced versus unvoiced—contribute to model decisions, offering crucial transparency for forensic applications. This research addresses a critical gap in the field: while deepfake detectors achieve high accuracy on benchmarks, they typically lack the explainability needed for legal and security contexts. In parallel, Khoury's work on "HAC-SLAM: Human Assisted Collaborative 3D-SLAM Through Augmented Reality" (2024, 4 citations) reimagines autonomous mapping by integrating human intelligence through AR interfaces, transforming SLAM from a purely algorithmic process into a collaborative human-machine system. By bridging audio security and spatial computing, Khoury demonstrates a rare ability to advance both theoretical understanding and practical deployment, making his research essential reading for anyone working at the frontiers of trustworthy AI and human-robot interaction.