Pietro Bonazzi
Papers
1
Total Citations
11
H-Index
1
About
Pietro Bonazzi is at the forefront of advancing wearable brain-computer interfaces (BCIs), with a primary focus on electroencephalogram (EEG)-based systems for motor imagery applications. His most-cited work, “On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface” (2024), tackles a critical challenge in the field: maintaining decoding accuracy across diverse users. By enabling on-device learning for lightweight neural networks, Bonazzi’s research bridges the gap between high-performance EEG decoding and practical, real-world deployment in rehabilitation and robotics. This contribution has already garnered 11 citations, reflecting its timely impact on making BCIs more adaptive and user-friendly. His work addresses key limitations in current systems—such as cross-subject variability—paving the way for personalized, wearable neurotechnology. Bonazzi’s research is particularly notable for its emphasis on real-time, resource-efficient learning, which is essential for moving BCIs from lab settings to everyday assistive devices. For students and researchers, his work represents a compelling intersection of machine learning, signal processing, and human-computer interaction, offering a blueprint for the next generation of intelligent, adaptive neural interfaces.
Research Focus
Key Achievements
Top Papers
- 1