Research

Publications and Preprints

2026

Optimal differentially private ranking from pairwise comparisons [Journal] [Preprint]
T. Tony Cai*, Abhinav Chakraborty*, Yichen Wang*. Journal of the American Statistical Association (2026) (* authors listed alphabetically)

Stability and Accuracy Trade-offs in Statistical Estimation [Preprint]
Abhinav Chakraborty* Yuetian Luo*, Rina Foygel Barber. arXiv preprint (2026) (* equal contribution)

Comparing three learn-then-test paradigms in a multivariate normal means problem [Preprint]
Abhinav Chakraborty* Junu Lee*, Eugene Katsevich. arXiv preprint (2026) (* equal contribution)

2025

Minimax and adaptive transfer learning for nonparametric classification under distributed differential privacy constraints [Journal] [Preprint] [Supplement]
Arnab Auddy*, T. Tony Cai*, Abhinav Chakraborty*. Journal of the Royal Statistical Society: Series B (2025) (* authors listed alphabetically)

When Data Can’t Meet: Estimating Correlation Across Privacy Barriers [PDF]
Abhinav Chakraborty, Arnab Auddy, T. Tony Cai. NeurIPS (Spotlight) (2025)

The Cost of Adaptation under Differential Privacy: Optimal Adaptive Federated Density Estimation [Preprint]
T. Tony Cai*, Abhinav Chakraborty*, Lasse Vuursteen*. arXiv preprint (2025) (* authors listed alphabetically)

Asymptotic Normality of Subgraph Counts in Sparse Inhomogeneous Random Graphs [Preprint]
Sayak Chatterjee, Anirban Chatterjee, Abhinav Chakraborty, Bhaswar B. Bhattacharya. arXiv preprint (2025)

Tackling Modern Challenges in Statistics: Integrating Privacy, Distributed Learning, and Data Heterogeneity [PDF] Abhinav Chakraborty. PhD thesis, University of Pennsylvania (2025)

2024

Reconciling model-X and doubly robust approaches to conditional independence testing [PDF]
Ziang Niu*, Abhinav Chakraborty*, Oliver Dukes, Eugene Katsevich. The Annals of Statistics (2024) (* equal contribution)

PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model [PDF]
Abhinav Chakraborty*, Anirban Chatterjee*, Abhinandan Dalal*. International Conference on Artificial Intelligence and Statistics (AISTATS) (2024) (* equal contribution)

Optimal Federated Learning for Functional Mean Estimation under Heterogeneous Privacy Constraints [Preprint]
Tony Cai*, Abhinav Chakraborty*, Lasse Vuursteen*. arXiv preprint (2024) (* authors listed alphabetically)

Doubly Robust and Computationally Efficient High-Dimensional Variable Selection [Preprint]
Abhinav Chakraborty*, Jeffrey Zhang*, Eugene Katsevich. arXiv preprint (2024) (* equal contribution)

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints [Preprint]
T. Tony Cai*, Abhinav Chakraborty*, Lasse Vuursteen*. arXiv preprint (2024) (* authors listed alphabetically)

Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests [Preprint]
T. Tony Cai*, Abhinav Chakraborty*, Lasse Vuursteen*. arXiv preprint (2024) (* authors listed alphabetically)

PriME: Privacy-aware Membership Profile Estimation in Networks [Preprint]
Abhinav Chakraborty, Sayak Chatterjee, Sagnik Nandy. arXiv preprint (2024)

2020

High Dimensional PCA: A New Model Selection Criterion [Preprint]
Abhinav Chakraborty, Soumendu Sundar Mukherjee, Arijit Chakrabarti. arXiv preprint (2020)