Publications
My doctoral research focuses on developing robust and efficient methodologies to evaluate causal excursion effects in sequential, adaptive intervention experiments. My work leverages new experimental approaches, such as micro-randomized trials (MRTs), as well as causal inference and supervised learning methods. The general theme of my research is to advance a more relevant, valid, and precise assessment of digital health intervention effects in the new context of time-varying treatments and repeated outcomes with clustering, interference, and high-dimensional nuisance parameters.
I was also part of the Virtual AppLication-supported ENvironment To INcrease Exercise (VALENTINE) Study, which aims to evaluate a digital intervention to supplement cardiac rehabilitation for low- and moderate risk patients, integrating a mobile application with physiologic and contextual information from wearables to provide incremental support to patients.
Since September 2023, I’ve been working on projects focused on developing data integration methods for Mendelian Randomization and conditional independence testing for Granger Causality. For a full list of my work, please see my Google Scholar profile.
Mobile Health (time-varying causal effect moderation)
- Cluster-level treatment effect heterogeneity and interference
- Incorporating auxiliary variables to improve the efficiency
- A meta-learning method and bidirectional asymptotics
Collaborative Work
- A randomized trial of a mobile health intervention to augment cardiac rehabilitation
- Contextually tailored text messages to augment cardiac rehabilitation: the Virtual AppLication-supported ENvironment To INcrease Exercise (VALENTINE) study
- Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention