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About

Xinglin Li is a pioneering researcher at the forefront of brain-computer interface (BCI) technology, specializing in EEG-based neural networks, adaptive edge AI, and multi-brain-to-multi-robot interaction. Their major contributions lie in developing intelligent systems that translate neural signals into real-world robotic control, bridging the gap between human thought and machine action. Li’s most-cited work, “Act as What You Think” (2023, 11 citations), introduces an attentional and embedded LSTM learning framework for personalized EEG interaction, advancing the dream of “mind-controlling” capabilities. Their subsequent studies, “NeuroBCI” (2024, 4 citations) and “BRIEDGE” (2024, 2 citations), push boundaries by enabling multi-brain collaboration with multiple robots through EEG-adaptive neural networks and semantic communication. These innovations promise transformative applications in home life and professional domains, where users can intuitively command robotic assistants using only their thoughts. Li’s work stands out for its emphasis on personalization and scalability, making BCI systems more practical and accessible. With a growing citation record and a clear trajectory toward real-world deployment, Xinglin Li is shaping the future of human-machine symbiosis, where thinking alone becomes a powerful form of action.