Email Address: email@example.com
I am a Research Associate at the MRC Biostatistics Unit, working with Sofia Villar on the use of multi-armed bandit strategies for designing novel trial designs such as adaptive clinical trials and micro-randomized trials (MRTs). MRTs are the current gold standard in the emergent area of mobile-Health (m-Health), where the goal is to optimally design mobile apps for guiding users’ behavior and improving their health outcomes. The design of such applications involves both the design of the trial and the design of the bandit algorithm.
As adaptive experiments such as m-Health apps or adaptive clinical trials usually have a dual goal of improving outcomes for participants enrolled into the experiment and learning about the effectiveness of interventions, estimation and inference in adaptively collected data play a central role in my research arena. We are currently exploring alternative hypothesis testing procedures for allowing reliable inference in adaptively collected data.
Currently, I am also a PhD Candidate in Methodological Statistics at University of Rome La Sapienza (Italy). During my PhD, I joined as a Visiting Research Scholar Bibhas Chakraborty’s lab at the National University of Singapore (Singapore), and Joseph J. Williams’s Intelligent Adaptive Interventions Lab at the Computer Science Department of University of Toronto (Canada). My research topics during my PhD lied at the intersection between Bayesian methods, statistical reinforcement learning & multi-armed bandits, and modern real-world applications based on adaptive decision making. These include dynamic treatment regimes (DRTs), m-Health, and adaptive experimentations.
In a previous life, I worked as a biostatistician at the GIMEMA Foundation (Rome), and I have been actively involved in cancer and health-related research projects, included European Organisation for Research and Treatment of Cancer (EORTC) projects.
- Williams, J. J., Nogas, J., Deliu, N., Shaikh, H., Villar, S. S., Durand, A., and Rafferty, A. Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments (2021), arXiv preprint arXiv:2103.12198.
- Figueroa C. A., Deliu N., Chakraborty B., Modiri A., Aggarwal J., Williams J. J., and Lyles C. R., Aguilera A. Daily Motivational Text-Messages to Promote Physical Activity in University Students: Results from a Micro-Randomized Trial. Annals of Behavioral Medicine (2021), DOI: 10.1093/abm/kaab028
- Figueroa, C. A., Aguilera A., Chakraborty B., Modiri A., Aggarwal J., Deliu N., Sarkar U., Williams J. J., and Lyles C. R. Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions. Journal of the American Medical Informatics Association (2021), DOI: 10.1093/jamia/ocab001
- Cottone, F., Deliu, N., Collins, G.S., Anota, A., Bonnetain, F., Van Steen, K., Cella, D. and Efficace, F. Modeling strategies to improve parameter estimates in prognostic factors analyses with patient-reported outcomes in oncology. Quality of Life Research, 28(5), pp.1315-1325 (2019)
- Cottone, F., Collins, G.S., Giesinger, J.M., Sommer, K., Deliu, N., Vignetti, M., Anota, A. and Efficace, F. The prognostic value of patient-reported outcomes (PROs) for survival outcomes in cancer patients: A systematic review. Journal of Clinical Oncology 2019 37:15_suppl, e18223-e18223 (2019)
- Sparano, F., Aaronson, N.K., Cottone, F., Piciocchi, A., La Sala, E., Anota, A., Deliu, N., Kieffer, J.M. and Efficace, F. Clinician-reported symptomatic adverse events in cancer trials: are they concordant with patient-reported outcomes?. Journal of comparative effectiveness research, 8(5), pp.279-288 (2019)
- Deliu, N., Cottone, F., Collins, G. S., Anota, A. and Efficace, F. Evaluating methodological quality of Prognostic models Including Patient-reported HeAlth outcomes iN oncologY (EPIPHANY): a systematic review protocol. BMJ open, 8(10), p.e025054 (2018)
- Ousmen, A., Touraine, C., Deliu, N., Cottone, F., Bonnetain, F., Efficace, F., Brédart, A., Mollevi, C. and Anota, A. Distribution-and anchor-based methods to determine the minimally important difference on patient-reported outcome questionnaires in oncology: a structured review. Health and quality of life outcomes, 16(1), p.228 (2018)
- Deliu, N., Efficace, F., Collins, G. S., Anota, A., Bonnetain, F., Van Steen, K., Cella, D., Cottone, F. Modelling strategies to improve estimates of prognostic factors analyses with patient reported outcomes: a simulation study. Quality Of Life Research 26 (1), 34-35 (2017)