Takuya Fujihashi

Papers

Total Citations

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About

Takuya Fujihashi is a leading researcher at the intersection of human–machine interaction, wireless communications, and signal processing. His work focuses on enabling seamless, low-latency communication between humans and remote robotic systems through efficient bioelectric signal transmission. Fujihashi’s major contributions include pioneering graph-based compression techniques for electroencephalography (EEG) signals, which outperform traditional methods like Discrete Wavelet Transform by preserving critical neural information while reducing data size—a breakthrough for real-time brain–computer interfaces. His most cited paper, "Graph-Based EEG Signal Compression for Human–Machine Interaction" (2023), has already garnered 6 citations, reflecting growing interest in his approach. Beyond EEG compression, Fujihashi has advanced semantic communication and multi-modal data transmission for immersive applications, including haptic and video feedback. His work has been published in top venues such as IEEE Transactions on Communications and ACM Multimedia, and he has received recognition for his contributions to next-generation wireless systems. With a citation count steadily rising, Fujihashi is shaping the future of how humans and machines interact through efficient, intelligent signal processing.