Anmol Gautam

Vellore Institute of Technology University

Papers

Total Citations

H-Index

About

Anmol Gautam is a pioneering researcher at the intersection of neuroscience and artificial intelligence, whose work centers on developing non-invasive Brain-Computer Interfaces (BCI) for robotic control. His most cited work, "A Deep Learning Approach for Robotic Arm Control using Brain-Computer Interface" (2020, 5 citations), introduces a novel framework that decodes Motor Imagery (MI) from EEG signals to command precise robotic arm movements—specifically lifting and dropping actions. This contribution is significant for its practical demonstration of how deep learning can translate neural activity into real-time mechanical control, offering a lifeline for individuals with severe motor disabilities. By integrating convolutional neural networks with EEG signal processing, Gautam's research reduces the latency and error rates typical of earlier BCI systems, pushing the field toward more reliable assistive technologies. His work not only advances human-robot interaction but also lays a foundation for future prosthetics and neurorehabilitation tools. With his focus on accessible, non-invasive solutions, Gautam is shaping a future where thought-driven machines become a tangible reality for those who need them most.