معرفی
Mahmoud Keshavarzi is a Researcher in the Department of Psychology at the University of Cambridge. His work focuses on neurodevelopmental disorders, particularly developmental language disorder (DLD) and dyslexia, combining EEG analysis with machine learning techniques. His research examines speech processing deficits in children, neural entrainment mechanisms, and the impact of environmental factors like screen time on auditory responsiveness. He develops innovative methods for speech signal analysis and noise reduction using deep learning approaches.
Key areas of investigation include:
- EEG-based neural markers for DLD and dyslexia
- Rhythmic speech processing in neurodevelopmental disorders
- Machine learning applications in clinical audiology
- Speech production and perception deficits in children
Notable contributions include EEG classification frameworks for infant speech processing and noise reduction algorithms improving speech intelligibility for cochlear implant users. His interdisciplinary work bridges cognitive neuroscience, signal processing, and developmental psychology.
