Sareh Saeedi
Papers
1
Total Citations
30
H-Index
1
About
Sareh Saeedi is a leading researcher in the field of brain-computer interfaces (BCIs), with a primary focus on enhancing the reliability and usability of electroencephalography (EEG)-based systems. Her key contributions lie in developing adaptive assistance mechanisms that predict command reliability in real time, addressing the critical challenge of performance variability in BCIs across different experimental sessions. Her seminal work, "Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability" (2016), has garnered 30 citations, reflecting its impact on improving BCI robustness for extended use. Saeedi’s research bridges machine learning and neural engineering, enabling more intuitive and stable control for users, particularly in motor imagery paradigms. Her achievements include pioneering methods to dynamically adjust BCI assistance based on user performance, which holds promise for assistive technologies and neurorehabilitation. By tackling the volatility of neural signals, Saeedi has advanced the practical deployment of BCIs, making her work essential for students and researchers aiming to create more adaptive and user-friendly neural interfaces.
Research Focus
Key Achievements
Top Papers
- 1