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About

Hilmi Yanar is a researcher specializing in brain-computer interfaces (BCI), electroencephalography (EEG) signal processing, and neural-controlled robotic systems. His work sits at the intersection of neuroscience and engineering, with a particular focus on developing non-invasive methods that translate human mental intent into precise robotic control. Yanar's most influential contribution is his 2018 dataset paper introducing a large EEG motor imagery dataset specifically designed to advance BCI research, which has garnered an impressive 174 citations and has become a foundational resource for researchers worldwide working to improve EEG-based systems. This work reflects his commitment to open, reproducible science that empowers the broader research community. Equally notable is his development of a three- to six-state EEG-based BCI system capable of controlling a virtual robotic manipulator with a remarkably short 15-minute training period — a practical breakthrough cited 39 times that brings non-invasive BCI closer to real-world clinical application. His earlier 2017 conference work laid the conceptual groundwork for this achievement. Collectively, Yanar's research makes meaningful strides toward accessible, high-performance prosthetic and assistive robotic systems controlled entirely through thought, offering transformative possibilities for individuals with motor disabilities.