Susan Murphy Receives 3 NIH Grants for Developing AI Methods in mHealth

Susan Murphy

The Department of Statistics is thrilled to share that Professor Susan Murphy, as part of a multi-PI, multi-institution team, recently secured three major NIH grant awards. These grants support cutting-edge research and include support for an mHealth (mobile health) center and developing digital just-in-time adaptive interventions for individuals with substance use disorders and dementia. Congratulations, Susan!

Here are the highlights of each award:

  • The mHealth Center for Discovery, Optimization, and Translation of Temporally-Precise Interventions: This center will develop multiple methodological and technological innovations, including easily deployable wearables, apps for wearables and smartphones, and software services. This award funds research by  Susan and her lab to develop autonomous, stable, and data efficient reinforcement learning algorithms to continuously personalize mHealth interventions with the goal of maximizing long-term therapeutic efficacy and engagement in real-life deployments. 

    Grant Details: Renewal | Lead Institution: University of Memphis (Harvard Subaward) | Aug 11, 2026 – Apr 30, 2031 

  • Methodologies for Adapting and Personalizing Services for SUD: This center focuses on methods and algorithmic development for designing and evaluating adaptive interventions and digital just-in-time adaptive interventions for prevention, early intervention, treatment, and recovery support for individuals with substance use disorders (SUDs). Susan's lab is funded to develop and deploy reinforcement learning algorithms targeting the supportive structure of the social network surrounding an individual with substance use problems.

    Grant Details: Renewal | Lead Institution: University of Michigan (Harvard Subaward) | Sep 1, 2026 – May 31, 2031 

  • mHealth intervention to promote physical activity in middle-aged and older adults to reduce the risk of Alzheimer's disease and related dementias: Physical activity (PA) is a key preventative strategy for dementia. However, the effectiveness of mHealth interventions for this typically declines by 6 to 12 months. Susan's lab is funded to develop and deploy reinforcement learning algorithms targeting slowing changing partially latent individual outcomes that are conjectured to lead to longer term physical activity.

    Grant Details: New Award | Lead Institution: University of Michigan (Harvard Subaward) | Sep 1, 2026 – Aug 31, 2031