[ Statistical Reinforcement Learning Lab | Research ]
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[ Harvard Stat Dept | Harvard CS Dept | Kempner Institute ]
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[Funding for Pilot Studies!]

Research Interests

The Statistical Reinforcement Learning Lab's work concerns the development of data analytic algorithms and methods for informing sequential decision making in health. In particular for (1) constructing individualized sequences of treatments (a.k.a., adaptive interventions) for use in informing clinical decision making and (2) constructing real time individualized sequences of treatments (a.k.a., Just-in-Time Adaptive Interventions) delivered by mobile devices. We are engaged in a number of clinical trials that use our real-time algorithms to learn and optimize the delivery of digital interventions. For her work on trial designs and analytics, Dr. Murphy was awarded a McArthur Fellowship in 2013, in 2014 she was elected a member of the National Academy of Medicine and in 2016 she was elected a member of the National Academy of Sciences of the US National Academies.

The lab's work is funded by National Institute on Drug Abuse , National Institute of Dental and Craniofacial Research , National Cancer Institute and by National Institute of Biomedical Imaging and Bioengineering. We work with researchers at d3Lab (ISR) and mDOT: mHealth Center for Discovery, Optimization & Translation of Temporally-Precise Interventions on these topics.