Multitarget tracking via restless bandit marginal productivity indices and Kalman filter in discrete time. - José Niño-Mora; Sofia S. Villar (CDC, 2009)

Sensor scheduling for hunting elusive hiding targets via whittle's restless bandit index policy. - José Niño-Mora; Sofia S. Villar (NetGCoop, 2011)

Opportunistic schedulers for optimal scheduling of flows in wireless systems with ARQ feedback. - Peter Jacko; Sofia S. Villar (ITC, 2012)

A Bayesian adaptive design for clinical trials in rare diseases. - S. Faye Williamson; Peter Jacko; Sofia S. Villar; Thomas Jaki (Comput. Stat. Data Anal., 2017)

Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints. - Cong Shen 001; Zhiyang Wang; Sofia S. Villar; Mihaela van der Schaar (ICML, 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)

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)

Some performance considerations when using multi-armed bandit algorithms in the presence of missing data. - Xijin Chen; Kim May Lee; Sofia S. Villar; David S. Robertson 001 (CoRR, 2022)

A comparison of allocation strategies for optimising clinical trial designs under variance heterogeneity. - Lida Mavrogonatou; Yuxuan Sun; David S. Robertson 001; Sofia S. Villar (Comput. Stat. Data Anal., 2022)

Computing the Performance of A New Adaptive Sampling Algorithm Based on The Gittins Index in Experiments with Exponential Rewards. - James K. He; Sofia S. Villar; Lida Mavrogonatou (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)

Exact statistical analysis for response-adaptive clinical trials: A general and computationally tractable approach. - Stef Baas; Peter Jacko; Sofia S. Villar (Comput. Stat. Data Anal., 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)