Vaibhav Gandhi
Papers
15
Total Citations
356
H-Index
8
About
Vaibhav Gandhi is a leading researcher at the intersection of brain-computer interfaces (BCI), assistive robotics, and human-robot interaction. His work focuses on creating non-muscular communication channels that allow individuals with severe motor impairments to control assistive devices using electroencephalogram (EEG) and electromyography (EMG) signals. Gandhi’s most influential contribution is the development of an adaptive brain–robot interface for mobile robot control, which addresses the critical bandwidth limitations of two-class BCI systems—a paper that has garnered 108 citations. He has also advanced the field through innovative signal processing techniques, including the use of recurrent quantum neural networks for EMG filtering, and has explored the design principles that make social robots effective interaction partners, as reflected in his highly cited 2020 review. Beyond BCI, Gandhi has contributed to swarm robotics fault detection and the development of EMG-controlled exoskeletons for strength augmentation. His work is characterized by a user-centric approach, emphasizing practical, low-cost solutions that bridge the gap between neural signals and real-world robotic control. With over 340 total citations across his publications, Gandhi’s research continues to shape the future of assistive and interactive robotics.
Research Focus
Key Achievements
Top Papers
- 1EEG-Based Mobile Robot Control Through an Adaptive Brain–Robot Interface108 citations · 2014
- 2What Makes a Social Robot Good at Interacting with Humans?74 citations · 2020
- 3Brain computer interface: A review46 citations · 2015
- 4Development of an EMG-Controlled Mobile Robot38 citations · 2018
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- 10Neuron-Based Control Mechanisms For A Robotic Arm And Hand5 citations · 2017