The Webinar Committee of the International Indian Statistical Association (IISA) proudly presents a webinar on " Reinforcement Learning Algorithms in Mobile Health Trials".
π Date: Friday, January 31, 2025
β° Time: 8:00 - 9:00 AM EST
π Location: Virtual (via Zoom)
Abstract: Mobile health (mHealth) β or more broadly, digital health β interventions (e.g., motivational text-messages or nudges to promote healthy behaviors) are becoming increasingly common in tandem with advances in mobile and wearable sensor technologies. In this talk, we will discuss an innovative trial design arising in mHealth, namely, the micro-randomized trial (MRT) that involves sequential, within-person randomization over many instances. The basic MRT design can be further improved to make it adaptive, thereby enabling it to learn from accumulated data as the trial progresses. This is appealing from an ethical perspective since the adaptive learning tends to make better interventions available to the trial participants. Adaptive learning in such trial designs is often operationalized via short-horizon Reinforcement Learning algorithms or contextual bandit algorithms. Specifically, we will discuss the role of a particular algorithm called Thompson sampling in designing adaptive MRTs. Theoretical as well as simulation results will be shown to validate the proposed approach. mHealth trials from the USA and the UK will be discussed as case studies.
Speaker Bio: Bibhas Chakraborty is a tenured Associate Professor and Director of the Center for Quantitative Medicine at the Duke-National University of Singapore Medical School (Duke-NUS), an Associate Professor of Statistics and Data Science at the National University of Singapore, and an Adjunct Associate Professor of Biostatistics and Bioinformatics at Duke University. Previously (2009-13), he was a tenure-track Assistant Professor of Biostatistics at Columbia University. He holds a B.Sc. (Statistics Hons.) from the University of Calcutta (2001), an M.Stat. from the Indian Statistical Institute (2003), and a Ph.D. in Statistics from the University of Michigan, Ann Arbor (2009). He is a recipient of the Calderone Research Prize for Junior Faculty from Columbia University in 2011, and the Young Statistical Scientist Award (Applications category) from the International Indian Statistical Association (IISA) in 2017. In 2022, he became an Elected Member of the International Statistical Institute (ISI). His core areas of research include dynamic treatment regimes, adaptive clinical trial designs, causal inference, reinforcement learning, interpretable machine learning for analysis of electronic health records, and mobile/digital health interventions in behavioral sciences. He authored the first textbook on dynamic treatment regimes (Springer, 2013) and co-edited a recent volume on statistical methods for precision medicine (Chapman and Hall/CRC, 2024). He currently serves as an Associate Editor of Biometrics.
Registration (free but required): https://weillcornell.zoom.us/webinar/register/WN_zE4Oys4jR3-aluXhZba8PA.
A flyer is attached to this post, and available for download at this link: https://www.dropbox.com/scl/fi/z9h2ztzrdxpjyzcch32o9/IISA-Flyer-Jan-2025.pptx?rlkey=tadxrugn04thavr21vcn5puhc&st=949r7j1b&dl=0.
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Himel Mallick, PhD, FASA
Principal Investigator (Tenure-track Faculty)
Cornell University
New York, New York 10065
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