Fernando Marmolejo‐Ramos

University of South Australia, University of Connecticut

Papers

Total Citations

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About

Fernando Marmolejo-Ramos is a leading researcher at the intersection of cognitive science, affective computing, and data science. His work focuses on understanding human emotions through physiological signals and advanced computational methods. A major contribution is the development of EDA-Graph, a novel framework that applies graph signal processing to electrodermal activity (EDA) for the continuous detection of emotional states. This approach, detailed in his most-cited 2024 paper (17 citations) and its 2023 precursor (4 citations), offers significant applications in mental health, marketing, human-computer interaction, and assistive robotics. By transforming raw EDA signals into graph-based representations, Marmolejo-Ramos enables more nuanced and real-time emotional recognition, overcoming limitations of traditional analysis. His work bridges psychophysiology and machine learning, providing tools for non-invasive emotional monitoring. With a growing citation impact, he is recognized for pioneering methods that decode the sympathetic nervous system’s role in emotion, making strides toward practical affective technologies. His research continues to inspire students and researchers in cognitive science and biomedical engineering.