معرفی
Tianchen Qian is an Assistant Professor in the Department of Statistics at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information & Computer Sciences. His research focuses on causal inference methodologies with applications in mobile health, clinical trials, and health-related behavioral interventions. He emphasizes the development of statistical frameworks for understanding treatment effects in longitudinal and time-varying contexts. Key collaborations involve multidisciplinary teams addressing challenges in real-time intervention delivery through mobile technologies.
Professor Qian’s methodological work includes advancing micro-randomized trial designs, causal excursion effect estimation, and reinforcement learning approaches for adaptive treatment strategies. His projects address critical questions such as optimizing intervention timing and content in mobile health apps, analyzing wearable sensor data for behavioral insights, and modeling cognitive decline in aging populations. Current studies involve applications in trauma-related anger management, cannabis craving reduction, and Alzheimer’s disease clinical trials.
His research bridges statistical innovation with healthcare practice, aiming to enhance the efficacy of digital interventions while minimizing participant burden. Notable methodological contributions include doubly robust estimation, semiparametric models, and adaptive enrichment designs for clinical trials. He is affiliated with UCI’s Center for Statistical Consulting and actively contributes to statistical education through courses on machine learning applications in behavioral science.
Recent work highlights include developing the Shift intervention for trauma-affected populations, analyzing step-count responses to real-time push notifications in mobile health, and exploring neuropathological correlates of cognitive decline in the 90+ Study. His team collaborates across disciplines to translate statistical breakthroughs into actionable health solutions.
