Saumitro Dasgupta

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About

Saumitro Dasgupta’s research lies at the intersection of brain-computer interfaces (BCIs) and assistive robotics, with a focus on noninvasive neural signal processing. His most cited work, a 2010 paper on a brain-controlled robotic platform using steady-state visual evoked potentials (SSVEP) acquired via EEG, exemplifies his commitment to translating complex neuroengineering concepts into practical, accessible systems. This capstone project, co-authored with fellow undergraduates, demonstrated how SSVEP-based BCIs could reliably command an iRobot platform, offering a low-cost, real-time control pathway for individuals with motor impairments. With 13 citations, the paper has influenced subsequent work in EEG-driven robotics and student-led neurotechnology initiatives. Dasgupta’s contribution is notable not only for its technical merit—integrating signal acquisition, feature extraction, and robotic actuation—but also for its educational impact, showcasing how undergraduate research can push the boundaries of human-machine interaction. His work underscores the potential of noninvasive BCIs to empower users through intuitive, brain-directed control, laying groundwork for future advancements in assistive technology and neural rehabilitation.