I am interested in applying data science and artificial intelligence tools that leverage dense longitudinal data from wearable, mobile, and connected devices to develop more effective health behavior interventions. The primary focus of this work involves an application of model predictive control tools from control systems engineering to develop person-specific text messaging algorithms (funded by NHLBI). We recentily extended that work to optimize generative artificial prompts to author messages that engage urges to move (as a part of the NIA-funded Roybal Center for Promoting Adherence to Behavior Change and Enhancing Cognitive Function). I recently two NIDDK-funded clinical trials on a computationally-simpler just-in-time adaptive intervention to promote fluid intake in patients with a history of kidney stones. We have applied unsupervised machine learning approaches to classify engagement with that intervention and its relations with biomarker changes as well.
I spent the first 25 years of my career at Penn State with a one-year adventure at Northwestern University. An unanticipated opportunity arose at Michigan and, after learning a bit more about it, I realized it would be invigorating to uproot, re-plant myself, and grow as a part of the scientific community here at Michigan. Thrilled to be here and looking forward to integrating more fully with the Michigan community.
I hope to develop approaches that make it more enjoyable and less effortful for people to do the ordinary behaviors that can have an extraordinary impact on their health.
I am excited about data science and AI research because of the insights we may be able to get from the digital exhaust that we all spew on a near-constant basis from our smartphones, wearables, and other connected devices.