Michael Sean Carroll

  • Source: Scopus
20022020

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Research Interests

My research is aimed at using computational methods to derive insight from large physiological datasets generated in clinical practice, with particular focus on pediatric autonomic and respiratory disorders, but recently expanding into critical care. My work has included familial dysautonomia, congenital central hypoventilation syndrome (CCHS), rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD), Rett syndrome and other pediatric disorders. My combined fluency with basic science, clinical and mathematical concepts inspires an eclectic and inclusive approach to discovery. Preferred quantitative tools span a wide range from traditional statistics through machine learning, network theory and dynamical system simulation. Nevertheless, these techniques are secondary to the central goal of understanding the physiological phenotype and underlying mechanisms of pediatric disorders, with the ultimate desire to improve patient care. I am also profoundly interested in bringing clinical physiology into the modern computational era by developing analytics and visualization systems that could provide physicians with tools to accelerate research, reduce healthcare costs and save lives. Such systems would be deeply transformative in specialty areas such as sleep medicine, neurophysiology, critical care, and of course, autonomic medicine. I’m currently collaborating with several physicians in critical care at Lurie to secure funding for continued development and further deployment of a visual analytics system to improve clinician situational awareness and patient monitoring in that department. For that project, I will be contributing to the development of physiologically relevant metrics and intuitive visualization techniques to facilitate important clinical decisions.

Education/Academic qualification

Computational Neuroscience, PhD, University of Chicago

… → 2009

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