David Haslacher

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About

David Haslacher is a rising figure in neural engineering, whose work bridges noninvasive brain-computer interfaces (BCIs) and sensory neuroprosthetics. His research focuses on minimizing biosignal recording sites to make hybrid brain/neural control systems more practical for real-world use, particularly for individuals with severe paralysis. In his highly cited 2020 paper, Haslacher demonstrated how to reduce the number of EEG and EOG electrodes without sacrificing control accuracy—a key step toward wearable, user-friendly assistive robots. Building on this, his 2021 work introduced a novel approach to sensory restoration: using artificial neural networks to model the brain’s visual system and derive optimized stimulation patterns for the optic nerve. By leveraging deep learning, he aims to restore complex sensory perception, such as sight, in neuroprosthetic users. Though early in his career, Haslacher’s contributions are already shaping the future of noninvasive neural control and sensory rehabilitation, with his work cited by researchers advancing both BCI hardware and computational models of the brain.