Publications

Nina Deliu, Joseph Jay Williams, Bibhas Chakraborty (2024). Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions. Article in International Statistical Review (Forthcoming).

Nina Deliu, Bibhas Chakraborty (2024). Artificial Intelligence-based Decision Support Systems for Precision and Digital Health. Book Chapter in Frontiers of Statistics and Data Science, IISA Series on Statistics and Data Science, Springer (Forthcoming).

Xinru Wang, Nina Deliu, Yusuke Narita, Bibhas Chakraborty (2024). Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials. Article in Biometrics (Forthcoming).

Harsh Kumar, Tong Li, Jiakai Shi, Ilya Musabirov, Rachel Kornfield, Jonah Meyerhoff, Ananya Bhattacharjee, Chris Karr, Theresa Nguyen, David Mohr, Anna Rafferty, Sofia Villar, Nina Deliu, Joseph Jay Williams (2024). Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health. Proceedings of the Thirty-Sixth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24). AAAI 2024.

Nina Deliu (2023). Multinomial Thompson sampling for rating scales and prior considerations for calibrating uncertainty. Article in Statistical Methods & Applications.

Ananya Bhattacharjee, Haochen Song, Xuening Wu, Justice Tomlinson, Mohi Reza, Akmar Ehsan Chowdhury, Nina Deliu, Thomas Price, Joseph Jay Williams (2023). Informing Users about Data Imputation. Exploring the Design Space for Dealing With Non-Responses. Proceedings at 11th AAAI Conference on Human Computation and Crowdsourcing HCOMP 2023.

Nina Deliu (2023). Reinforcement learning for sequential decision making in population research. Article in Quality and Quantity.

Nina Deliu (2023). Multiculturality and Interculturality: Qualitative Analysis of the Perspective of Focus Group Participants. Book Chapter in Education in Multiculturality, Education to Interculturality. Urbaniana University Press, Città del Vaticano ISBN 978-88-401-9061-7.

Xueqing Liu, Nina Deliu, Bibhas Chakraborty (2023). Microrandomized Trials: Developing Just-in-Time Adaptive Interventions for Better Public Health. Article in American Journal of Public Health.

PDF DOI Presentation

Nina Deliu, Bibhas Chakraborty (2022). Dynamic Treatment Regimes for Optimizing Healthcare. Book Chapter in The Elements of Joint Learning and Optimization in Operations Management, pages 391–444. Springer.

PDF Project DOI

Isabel Chien, Nina Deliu, Richard Turner, Adrian Weller, Sofia Villar, Niki Kilbertus (2022). Multi-disciplinary fairness considerations in machine learning for clinical trials. In FAccT ‘22 – 2022 ACM Conference on Fairness, Accountability, and Transparency.

PDF DOI Presentation

Caroline A Figueroa, Nina Deliu, Bibhas Chakraborty, Arghavan Modiri, Jing Xu, Jai Aggarwal, Joseph Jay Williams, Courtney Lyles, Adrian Aguilera (2022). Daily Motivational Text Messages to Promote Physical Activity in University Students: Results From a Microrandomized Trial. Article in Annals of Behavioral Medicine.

Caroline A Figueroa, Adrian Aguilera, Bibhas Chakraborty, Arghavan Modiri, Jai Aggarwal, Nina Deliu, Urmimala Sarkar, Joseph Jay Williams, Courtney R Lyles (2021). Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions. Article in Journal of the American Medical Informatics Association.