Research Interests

• High-dimensional statistics

• Graphical models and network data

• Fluctuation theory and dependent observations

• Random matrix theory

• Statistical problems in single-cell genomics

Publications

1. Abhinav Chakraborty^*, Sayak Chatterjee^*, and Sagnik Nandy^*. “PriME: Privacy-Aware Membership Profile Estimation in Networks.” SIAM Journal on Mathematics of Data Science, 8(3):1029–1061, 2026.

2. Soham Bonnerjee, Zhen Wei (Kingsley) Yeon, Anna Asch, Sagnik Nandy, and Promit Ghosal. “How Private is Your Attention? Bridging Privacy with In-Context Learning.” Transactions on Machine Learning Research, 2026.

3. Dominik Meier, Shixing Yu, Sagnik Nandy, Promit Ghosal, and Kyra Gan. “Clustering by Denoising: Latent Plug-and-Play Diffusion for Single-Cell Data.” In Proceedings of the International Conference on Learning Representations (ICLR), 2026. [ GitHub ]

4. David Kogan, Sagnik Nandy, and Jiaoyang Huang. “Extremal Eigenvalues of Random Kernel Matrices with Polynomial Scaling.” Random Matrices: Theory and Applications, 14(4):2550020, 2025.

5. Sagnik Nandy and Subhabrata Sen. “Bayes Optimal Learning in High-Dimensional Linear Regression with Network Side Information.” IEEE Transactions on Information Theory, 71(1):565–591, 2025.

6. Anirban Chatterjee, Sagnik Nandy, and Ritwik Sadhu. “Detecting Planted Partition in Sparse Multilayer Networks.” Information and Inference: A Journal of the IMA, 13(3):iaae019, 2024. [ GitHub ]

7. Sagnik Nandy and Bhaswar B. Bhattacharya. “Degree Heterogeneity in Higher-Order Networks: Inference in the Hypergraph β-Model.” IEEE Transactions on Information Theory, 70(8):6000–6024, 2024.

8. Arnab Auddy^*, Nabarun Deb^*, and Sagnik Nandy^*. “Exact Detection Thresholds and Minimax Optimality of Chatterjee’s Correlation Coefficient.” Bernoulli, 30(2):1640–1668, 2024.

9. Zongming Ma and Sagnik Nandy. “Community Detection with Contextual Multilayer Networks.” IEEE Transactions on Information Theory, 69(5):3203–3239, 2023.

Preprints

1. Sagnik Nandy, Samriddha Lahiry, Pragya Sur, and Subhabrata Sen. “DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing.” arXiv preprint arXiv:2608.02769, 2026. [ GitHub ]

2. Abhinav Chakraborty^* and Sagnik Nandy^*. “Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data.” arXiv preprint arXiv:2607.25031, 2026. [ GitHub ]

3. Sagnik Nandy^*, Wanyi Ling^*, and Nikolaos Ignatiadis. “How Does limma-trend Work? An Empirical Partially Bayes Perspective.” arXiv preprint arXiv:2605.21304, 2026. [ GitHub ]

4. Bibhabasu Mandal and Sagnik Nandy. “Privacy–Utility Trade-Offs for Parameter Estimation in Degree-Heterogeneous Higher-Order Networks.” arXiv preprint arXiv:2602.03948, 2026. [ GitHub ]

5. Sagnik Nandy and Zongming Ma. “Multimodal Data Integration and Cross-Modal Querying via Orchestrated Approximate Message Passing.” arXiv preprint arXiv:2407.19030, 2024. [ GitHub ]

^* Equal contribution.

See also my Google Scholar profile.