Researcher · Division of Health AI
Shubham Debnath is a Senior Research Scientist at the Feinstein Institutes for Medical Research with expertise in autonomic nervous system quantification and bioelectronic medicine. His research focuses on developing methods to modulate the autonomic nervous system function and quantify responses using non-invasive sensors, as well as clinical applications including maternal fever prediction, COVID-19 clinical decision support systems, and analysis of chronic vagus nerve recordings. Debnath has contributed to peer-reviewed publications on autonomic function assessment methodologies and their translational applications in clinical care.
5 projects8 papers

Research projects
Continuously monitored vital signs and heart rate variability during labor predict maternal fever 2-3 hours before clinical onset, with area under the curve of 0.748, enabling early detection of mothers at risk for neonatal early-onset sepsis.
Point-of-care AI
Machine learning models identify PTSD from non-invasive physiological signals, including heart rate variability, in a study currently under review. The lab also studies transcutaneous auricular vagus nerve stimulation as a potential PTSD treatment for World Trade Center responders with limited response to existing therapies.
Autonomic Nervous System AI
Chronic wireless recording of compound action potentials from the mouse vagus nerve up to 6 months, enabling longitudinal tracking of neural activity in disease models (CIA, CAIA) to predict inflammation severity and evaluate neuromodulation efficacy.
Preclinical AI
Publications
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