Gleni Lamani

Friedrich-Alexander-Universität Erlangen-Nürnberg

Papers

Total Citations

H-Index

About

Gleni Lamani’s research lies at the intersection of acoustic signal processing and robotics, with a primary focus on developing advanced beamforming techniques for robotic auditory systems. Her most cited work, “HRTF-based robust least-squares frequency-invariant beamforming” (2015, 13 citations), introduces a novel approach that integrates Head-Related Transfer Functions (HRTFs) into a Robust Least-Squares Frequency-Invariant (RLSFI) beamformer design. This innovation addresses a critical challenge in robot hearing: the distortion of sound fields caused by a robot’s own head structure. By accounting for HRTF effects, Lamani’s beamformer significantly improves spatial audio capture and source localization in real-world environments, enabling robots to better interpret complex acoustic scenes. Her contributions have been recognized for their practical impact on human-robot interaction and autonomous navigation, where accurate sound processing is essential. With a growing citation record, Lamani’s work continues to influence researchers in acoustic array processing and robotics, offering a robust foundation for future advancements in intelligent auditory systems. Her dedication to bridging theoretical signal processing with tangible robotic applications marks her as a promising voice in the field.