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This Research Investigator specializes in developing advanced bi-directional neural interfaces, contributing to the forefront of systems neuroscience and intelligent neurotechnology. Their work focuses on creating interfaces that both record and stimulate neural circuits, enabling deeper understanding of brain function and paving the way for next-generation neuroprosthetics, cognitive augmentation tools, and brain–machine communication systems. At The Standard School of Machine Learning (TheSSML), they integrate principles of neural engineering, computational modeling, and machine learning to design technologies capable of decoding and modulating neural signals with precision. Their interdisciplinary approach advances research in brain behavior prediction, closed-loop neuromodulation, and adaptive neural interface design, helping students explore the future of AI-enabled neuroscience and human–machine integration.