Amit Singhal

Netaji Subhas University of Technology, University of Rochester

Papers

Total Citations

102

H-Index

About

Amit Singhal is a researcher whose work bridges the foundational principles of probabilistic reasoning with the cutting-edge challenges of brain-computer interfaces (BCIs). His research primarily focuses on multimodal sensor fusion, Bayesian evidence combination, and EEG-based motor imagery signal analysis. Singhal’s major contributions include pioneering the use of dynamic Bayesian networks for integrating data from multiple sensors on autonomous mobile robots, a framework that offered quantifiable advantages over neural networks for high-level vision tasks. More recently, he has advanced the field of BCI by developing deep temporal networks for recognizing motor imagery from noisy, non-stationary EEG signals. His comprehensive 2023 review on EEG-based motor imagery, which has already garnered 45 citations, serves as a definitive resource for researchers in robotics, gaming, and medical applications. With over 100 total citations across his most-cited works, Singhal’s impact lies in his ability to combine rigorous probabilistic modeling with practical signal processing, making him a key figure in both autonomous systems and neural engineering.