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About

Patrick A. Naylor is a distinguished researcher whose work sits at the intersection of acoustic signal processing, robot audition, and spatial audio technologies. His research has fundamentally advanced how machines perceive, localize, and interact with sound in complex real-world environments, with particular focus on microphone array processing, acoustic source localization and tracking, and speech enhancement. Among his most impactful contributions is his pioneering work on Acoustic SLAM — a novel framework enabling microphone-equipped robots to simultaneously map their acoustic environment and localize sound sources in three dimensions, garnering 103 citations. Equally influential is his co-development of the LOCATA Challenge Data Corpus, a landmark benchmark dataset that standardized evaluation of acoustic localization and tracking algorithms across the research community, also drawing 103 citations. His broader portfolio addresses bearing-only speaker tracking, adaptive beamforming, speech dereverberation using polynomial eigenvalue decomposition, and spherical microphone array processing — all critical capabilities for robust human-robot interaction. Naylor's work consistently bridges theoretical rigor and practical application, with relevance spanning hearing aids, teleconferencing, smart home systems, and autonomous robots. His research has helped establish the methodological foundations that newer generations of spatial audio and robot audition researchers continue to build upon.