Imali Hettiarachchi
Papers
2
Total Citations
37
H-Index
2
About
Dr. Imali Hettiarachchi is a pioneering researcher at the intersection of neural engineering and human-autonomy systems. Her work primarily focuses on brain-computer interfacing (BCI), specifically advancing Steady-State Visual Evoked Potential (SSVEP) classification, and the emerging field of trust dynamics in human-autonomy teaming (HAT). Her most cited paper, "A time domain classification of steady-state visual evoked potentials using deep recurrent-convolutional neural networks" (2018, 33 citations), tackles a core BCI challenge by introducing a novel deep learning architecture that processes raw EEG signals in the time domain, significantly improving the translation of neural activity into actionable commands. This contribution has been foundational for developing more intuitive and responsive BCI systems. More recently, Dr. Hettiarachchi has ventured into the critical area of trust assessment in autonomous systems with her 2025 review, which systematically categorizes subjective and objective metrics for evaluating trust in human-autonomy teams. This work is vital for designing safer, more effective collaborative robots and AI. Her research bridges technical signal processing with human factors, positioning her as a key voice in creating seamless human-machine partnerships.
Research Focus
Key Achievements
Top Papers
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