Mingzhu Wu

Papers

Total Citations

H-Index

About

Mingzhu Wu is a rising researcher at the forefront of brain-computer interfaces (BCI) and human-robot collaboration, pioneering systems that allow multiple individuals to control multiple robots using only their thoughts. Her work centers on integrating EEG-based neural networks with edge AI and semantic communications to create practical, scalable BCI solutions. Wu’s major contributions include the development of DeepBrain (2022, 9 citations), a foundational framework combining BCI with robotic systems to assist mobility-impaired users. She later advanced this vision with NeuroBCI (2024, 4 citations), introducing multi-brain to multi-robot interaction through EEG-adaptive neural networks and semantic communications, enabling collaborative control in home environments. Her latest system, BRIEDGE (2024, 2 citations), establishes an end-to-end edge AI architecture for real-time, multi-user brain-to-robot interaction, addressing critical challenges in sensing, computing, and control integration. With cumulative citations growing rapidly, Wu’s work is shaping the future of assistive robotics and collaborative BCI systems. Her innovative approach to merging adaptive AI with neural signal processing positions her as a key contributor to next-generation human-machine interfaces.