معرفی
Daniel Almirall is a Research Associate Professor at the University of Michigan's Institute for Social Research (ISR) and holds a courtesy appointment in the Department of Statistics. He co-directs the Data Science for Dynamic Intervention Decision-making Center (d3c), focusing on developing statistical methods for adaptive interventions in healthcare and education. With a Ph.D. in Statistics from the University of Michigan (2007), his career includes roles at Duke University and the Durham VA Center for Health Services Research.
His research emphasizes adaptive interventions—dynamic treatment strategies optimized via Sequential Multiple Assignment Randomized Trials (SMARTs)—to address chronic health conditions, mental health (e.g., autism, depression), and substance abuse. Key contributions include methodological frameworks for causal inference, longitudinal data analysis, and implementation science. Notable recognition includes a Top 20 Autism Article (2016) and a US Department of Education-recognized methodology publication (2020).
Almirall advises students across statistics, biostatistics, and education, mentoring over a dozen PhD, master’s, and undergraduate researchers. His work bridges theory and practice, collaborating with clinicians and educators to deploy evidence-based interventions. Ongoing efforts focus on scalable strategies for schools and clinics to adopt adaptive interventions, leveraging d3c's collaborative environment.
