معرفی
Nina Deliu is a Tenure-track Assistant Professor in Statistics at Sapienza University of Rome's MEMOTEF Department, with joint appointments as a Visiting Faculty Researcher at Google and Visiting Researcher at the MRC-Biostatistics Unit, University of Cambridge. She holds editorial roles at Trials journal and YoungStatS, and maintains active collaborations with institutions including the University of Toronto, National University of Singapore, ISTAT, NADO Italia, and FAO.
Education:
- PhD in Methodological Statistics, Sapienza University of Rome (2021)
- MSc in Statistics and Decisions, Sapienza University of Rome (2017)
- MSc in Mathématiques, Informatique, Décision et Organisation, Université Paris Dauphine (2016)
Research spans Bayesian inference, reinforcement learning, multi-armed bandits, adaptive experimental design, copula models, and uncertainty quantification, with applications in healthcare, education, and public health. Her work bridges theoretical statistics with real-world challenges in biostatistics, mobile health interventions, and digital education platforms.
Publications focus on adaptive experimentation frameworks, response-adaptive clinical trials, reinforcement learning in healthcare, and copula-based statistical methods. Recent work emphasizes finite-sample error control, zero-inflated count data modeling, and multivariate dependency analysis.
Awards:
- XPRIZE $1M Digital Learning Challenge (2023) for the Adaptive Experimentation Accelerator project
Research Projects:
- The role of self-reported health outcomes in cancer risk prediction using UK Biobank data
- Contextual Multi-armed Bandits for Developing Personalized Mobile Health Interventions
Leads collaborations through the IAI Lab (University of Toronto) and coordinates interdisciplinary teams for projects in statistical methodology, health interventions, and official statistics innovation.
