Challenges and opportunities of using reinforcement learning to optimize behavioral health interventions delivered via smartphones. - Caroline A. Figueroa; Adrián Aguilera; Bibhas Chakraborty; Arghavan Modiri; Jai Aggarwal; Nina Deliu; Urmimala Sarkar; Joseph Jay Williams; Courtney R. Lyles (AMIA, 2020)

Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments. - Joseph Jay Williams; Jacob Nogas; Nina Deliu; Hammad Shaikh; Sofia S. Villar; Audrey Durand; Anna N. Rafferty (CoRR, 2021)

Efficient Inference Without Trading-off Regret in Bandits: An Allocation Probability Test for Thompson Sampling. - Nina Deliu; Joseph Jay Williams; Sofia S. Villar (CoRR, 2021)

Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization. - Jacob Nogas; Tong Li; Fernando J. Yanez; Arghavan Modiri; Nina Deliu; Ben Prystawski; Sofia S. Villar; Anna N. Rafferty; Joseph Jay Williams (CoRR, 2021)

Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions. - Caroline A. Figueroa; Adrián Aguilera; Bibhas Chakraborty; Arghavan Modiri; Jai Aggarwal; Nina Deliu; Urmimala Sarkar; Joseph Jay Williams; Courtney R. Lyles (J. Am. Medical Informatics Assoc., 2021)

Multi-disciplinary fairness considerations in machine learning for clinical trials. - Isabel Chien; Nina Deliu; Richard E. Turner; Adrian Weller; Sofia S. Villar; Niki Kilbertus (FAccT, 2022)

Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions. - Nina Deliu; Joseph Jay Williams; Bibhas Chakraborty (CoRR, 2022)

Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study. - Xueqing Liu; Nina Deliu; Tanujit Chakraborty; Lauren Bell; Bibhas Chakraborty (CoRR, 2023)

Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health. - Harsh Kumar; Tong Li; Jiakai Shi; Ilya Musabirov; Rachel Kornfield; Jonah Meyerhoff; Ananya Bhattacharjee; Chris J. Karr; Theresa Nguyen; David C. Mohr; Anna N. Rafferty; Sofia S. Villar; et al. (AAAI, 2024)

Anomaly Detection in Multivariate Profiles with Conformal Bayesian Inference. - Nina Deliu; Brunero Liseo (COPA, 2024)

Artificial Intelligence-based Decision Support Systems for Precision and Digital Health. - Nina Deliu; Bibhas Chakraborty (CoRR, 2024)

Platform-based Adaptive Experimental Research in Education: Lessons Learned from The Digital Learning Challenge. - Ilya Musabirov; Mohi Reza; Haochen Song; Steven Moore; Pan Chen; Harsh Kumar; Tong Li; John C. Stamper; Norman L. Bier; Anna N. Rafferty; Thomas W. Price; Nina Deliu; et al. (LAK, 2025)

A copula-based Bayesian framework for doping detection. - Nina Deliu; Brunero Liseo (Comput. Stat., 2025)

A Personalized Exercise Assistant using Reinforcement Learning (PEARL): Results from a four-arm Randomized-controlled Trial. - Amy A. Lee; Narayan Hegde; Nina Deliu; Emily Rosenzweig; Arun Sai Suggala; Sriram Lakshminarasimhan; Qian He; John Hernandez; Martin Seneviratne; Rahul Singh; Pradnesh Kalkar; Karthikeyan Shanmugam; et al. (CoRR, 2025)