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Rishi Kamaleswaran is an Associate Professor at the Duke Pratt School of Engineering. His research focuses on the application of artificial intelligence and machine learning in healthcare, particularly in critical care and perioperative medicine. He has published numerous papers on developing predictive models for sepsis and acute respiratory distress syndrome. His work utilizes large datasets, electronic health records, and physiological waveform analysis to enhance patient outcomes. He has explored deep learning techniques for disease diagnosis and prediction, including the detection of cardiac arrhythmias and Parkinson's disease. Additionally, his research investigates wearable sensors for remote patient monitoring to improve healthcare delivery. Kamaleswaran has collaborated with clinicians and researchers, validating and translating models for clinical practice. Overall, his goal is to leverage data-driven approaches to transform healthcare and improve patient care.
Duke University • Durham, NC
Teaching and conducting research in fields related to trauma, critical care, and healthcare technologies.
Department of Biomedical Engineering (MS program)