Susan Murphy’s research focuses on improving sequential, individualized, decision making in health, in particular, clinical trial design and data analysis to inform the development of just-in-time adaptive interventions in digital health. She developed the micro-randomized trial for use in constructing digital health interventions; this trial design is in use across a broad range of health-related areas. Her lab works on online learning algorithms for developing personalized digital health interventions. Dr. Murphy is a member of the National Academy of Sciences and of the National Academy of Medicine, both of the US National Academies. In 2013 she was awarded a MacArthur Fellowship for her work on experimental designs to inform sequential decision making. She is a Past-President of IMS and of the Bernoulli Society and a former editor of the Annals of Statistics.

Research Interests

Susan Murphy's lab works on how to design trials and analyze the resulting data so as to personalize and adapt sequences of interventions to the individual. This is particularly useful when individuals are suffering from a chronic disorder in which treatment needs to adapted to the individual over time. They developed a new type of randomized trial, the sequential, multiple assignment randomized trial which has now been deployed across many areas of health including the treatment of substance use disorders, attention deficit disorders, depression, alcohol use disorders, obesity, obsessive compulsive disorders, insomnia, bipolar disorders, autism spectrum disorders and also in implementation science to improve the implementation of evidence based mental health treatment. The lab currently focuses on mobile health in which a sequence of in-the-moment supportive interventions might be provided to an individual over time. The lab has developed a randomized trial, the "micro-randomized trial" and associated data analytic methods that can be used to optimize the timing and content of the sequence of supportive interventions. The lab is also working on online data analytic methods for use in personalizing the timing and content of mobile interventions as the individual uses the mobile device and data is collected in real time.

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Primary Section

Section 53: Social and Political Sciences

Secondary Section

Section 32: Applied Mathematical Sciences