R. Chandramouli

University of Maryland, Baltimore County

Papers

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About

R. Chandramouli is a rising researcher at the intersection of biomedical signal processing and affective computing, with a primary focus on emotion recognition using electroencephalography (EEG). His most notable contribution is a pioneering study on Transformer-based emotion recognition from EEG signals, which introduces a tailored deep-learning architecture to predict valence and arousal levels—key dimensions of human emotion. This work, published in 2024 and already garnering 5 citations, demonstrates his ability to apply state-of-the-art machine learning techniques to decode complex neural data, offering a promising pathway for non-invasive affective state assessment. Chandramouli’s research holds significant potential for applications in mental health monitoring, brain-computer interfaces, and human-computer interaction. By bridging advanced transformer models with biomedical signal processing, he is contributing to a growing body of work that seeks to make emotion recognition more accurate and scalable. As an emerging voice in this field, his early impact signals a trajectory of continued influence in the development of intelligent, brain-driven technologies.