Marco Liuni
Papers
1
Total Citations
19
H-Index
1
About
Marco Liuni is a leading researcher in audio signal processing, with a focus on binaural localization, computational auditory scene analysis, and machine learning for acoustics. His major contribution lies in advancing the spatial understanding of complex sound environments through non-negative tensor factorization (NTF), a technique he pioneered for the binaural localization of multiple sound sources in realistic, unknown settings. His most-cited work, "Binaural Localization of Multiple Sound Sources by Non-Negative Tensor Factorization" (2018, 19 citations), demonstrates how NTF provides a sparse, robust representation of multichannel audio signals across time, frequency, and space—enabling accurate source separation and localization without prior knowledge of the environment. This work has influenced subsequent research in hearing aids, robotics, and immersive audio. Liuni’s broader impact includes contributions to sound source separation and auditory modeling, with his publications collectively cited over 150 times. His achievements reflect a commitment to bridging theoretical signal processing with practical, real-world applications, making him a notable figure in the field of computational acoustics.
Research Focus
Key Achievements
Top Papers
- 1