Mike Chung
Papers
6
Total Citations
124
H-Index
4
About
Mike Chung is a pioneering researcher in the field of brain-computer interfaces (BCIs) for robotic control, with a particular focus on non-invasive, EEG-based systems. His major contributions center on developing adaptive, hierarchical control architectures that bridge the gap between low-bandwidth neural signals and high-degree-of-freedom robotic platforms. In his most cited work, "An adaptive brain-computer interface for humanoid robot control" (61 citations), Chung demonstrated a novel approach that moves beyond fixed, pre-wired behaviors to enable more flexible, low-level control of humanoid robots. He further advanced the field by creating methods for automatic extraction of command hierarchies (19 citations) and exploring uncertainty-based interaction between humans and robots to mitigate the fatigue and tedium associated with moment-by-moment neural control. Chung’s research also extends to multimodal interfaces, including continuous vocalization control for assistive robots. His work has been instrumental in making BCI-driven robotic control more practical and user-friendly, directly addressing the core challenge of low signal-to-noise ratio in non-invasive systems. Through his adaptive and hierarchical frameworks, Chung has laid essential groundwork for the next generation of assistive and humanoid robotics.
Research Focus
Key Achievements
Top Papers
- 1An adaptive brain-computer interface for humanoid robot control61 citations · 2011
- 2Non-invasive Brain-Computer Interfaces: Enhanced Gaming and Robotic Control28 citations · 2011
- 3
- 4Towards hierarchical BCIs for robotic control11 citations · 2011
- 5Continuous vocalization control of a full-scale assistive robot3 citations · 2012
- 6