Modern Experimental Design and Active Learning in the Real World
Hongseok Namkoong
Deployable RL Workshop @ RLC 2024
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Much of my research has focused on developing methods for statistical inference for data collected with bandit and reinforcement learning algorithms, i.e., adaptively collected data. Since fall 2020, I have also been working to design the reinforcement learning algorithm and statistical inference approach to be used for the primary analysis for Oralytics, a mobile health micro-randomized trial for oral health coaching in collaboration with Oral-B and researchers at UCLA and UMichigan.
Experience Developing and Deploying RL Algorithms: I also have experience collaborating with domain scientists in running and designing online RL algorithms for mobile health interventions; these interventions involve delivering personalized support through wearables and smart devices to help users in managing a variety of chronic health problems in an ``in-the-moment'' fashion. Specifically, since fall 2020 I have been involved in Oralytics, a mobile health micro-randomized trial for oral health coaching i
Modern Experimental Design and Active Learning in the Real World
Hongseok Namkoong
Deployable RL Workshop @ RLC 2024