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About

H. Reynolds is a researcher at the forefront of assistive robotics, specializing in brain-computer interfaces (BCI) and advanced additive manufacturing. Their work centers on decoding neural signals to enable intuitive human-robot interaction, particularly for individuals with motor impairments. Reynolds’ key contributions include a comparative study of one-handed versus two-handed EEG intent recognition, demonstrating how machine learning can classify brain activity to control robotic systems—a critical step toward restoring autonomy for disabled users. With over 3 citations for this work, they have helped validate BCI performance metrics for real-world human-robot interaction. Beyond neural interfaces, Reynolds has pioneered rapid prototyping techniques through the NeXus system, a robotic additive manufacturing platform that produces multiscale flexible printed circuit boards. This innovation, showcased in their 2024 paper, bridges the gap between custom electronics and scalable fabrication. By combining BCI research with hardware manufacturing, Reynolds is shaping a future where adaptive, user-centered robotics are both intelligent and accessible.