Research

Research interests

My research interests lie in distribution-free inference, multiple testing, and variable selection. My current research primarily focuses on developing theoretically efficient and practically applicable methods that effectively address the challenges of model-free inference.

Publications

Online monotone density estimation and log-optimal calibration.

Rohan Hore, Ruodu Wang and Aaditya Ramdas.

To appear in COPA, 2026.

arXiv
One-shot conditional sampling: MMD meets nearest neighbors.

Anirban Chatterjee, Sayantan Choudhury and Rohan Hore.

International Conference on Machine learning, 2026.

arXiv Code Conference
Conformal prediction with local weights: randomization enables local guarantees.

Rohan Hore and Rina Foygel Barber.

Journal of the Royal Statistical Society Series B, 2024.

arXiv Code Journal
Conformalized survival analysis with adaptive cutoffs.

Yu Gui, Rohan Hore, Zhimei Ren, and Rina Foygel Barber.

Biometrika, 2023.

arXiv Code Journal
Robust and Efficient Parameter Estimation for Discretely Observed Stochastic Processes.

Rohan Hore and Abhik Ghosh.

Annals of the Institute of Statistical Mathematics, 2024.

arXiv Code Journal

Preprints

Local permutation tests for conditional independence: an adaptive binning perspective.

David Chen, Rohan Hore and Rina Foygel Barber.

arXiv Code
Distribution-free root cause analysis.

Rohan Hore and Aaditya Ramdas.

arXiv Code
Distribution-free two-sample testing with blurred total variation distance.

Rohan Hore and Rina Foygel Barber.

arXiv Code
Conformal changepoint localization.

Rohan Hore and Aaditya Ramdas.

arXiv Code
Testing conditional independence under isotonicity.

Rohan Hore, Jake A. Soloff, Rina Foygel Barber and Richard J. Samworth.

arXiv Code