Sengupta, S., Khamaru, K., Ghosh, S., Dasgupta, T. (2026). Design Stability in Adaptive Experiments: Implications for Treatment Effect Estimation. In: Biometrika 113.3.
Develops a framework for valid causal inference under adaptive treatment assignment, introducing design stability and establishing asymptotic guarantees.
Ghosh, S., Khamaru, K., Dasgupta, T. (2025). PICS: A sequential approach to obtain optimal designs for non-linear models leveraging closed-form solutions for faster convergence. In: Technometrics 68.2, pp. 282–294.
Introduces PICS, a hybrid sequential strategy for D-optimal designs using closed-form solutions to improve efficiency and convergence.
Lin, L., Ying, M., Ghosh, S., Khamaru, K., Zhang, C.-H. (2023). Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference. In: Advances in Neural Information Processing Systems, Vol. 36. Curran Associates, Inc.
Explores estimation and inference limits in adaptive linear models, highlighting challenges for low-dimensional parameter estimation.