activity
20222026
most citedImputation under Differential Privacy

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2026

Differential Privacy Guarantees in Small Area Estimation

Soumojit Das, Jörg Drechsler

Statistical agencies increasingly rely on small area estimation to produce reliable estimates for subpopulations with limited sample sizes. These estimates are built from individua…

stat.ML2025

Geometric Calibration and Neutral Zones for Uncertainty-Aware Multi-Class Classification

Soumojit Das, Nairanjana Dasgupta, Prashanta Dutta

Modern artificial intelligence systems make critical decisions yet often fail silently when uncertain -- even well-calibrated models provide no mechanism to identify \textit{which…

stat.ME2025

Multidimensional Poverty Mapping for Small Areas

Soumojit Das, Dilshanie Deepawansa, Partha Lahiri

Many countries measure poverty based only on income or consumption. However, there is a growing awareness of measuring poverty through multiple dimensions that captures a more reas…

stat.ME2022★ 1 cited

Approximate hierarchical Bayes small area estimation using NEF-QVF and poststratification

Soumojit Das, Partha Lahiri

We propose an approximate hierarchical Bayes approach that uses the Natural Exponential Family with Quadratic Variance Function in combining information from multiple sources to im…

cs.DB2022★ 4 cited

Imputation under Differential Privacy

Soumojit Das, Jorg Drechsler, Keith Merrill +1

The literature on differential privacy almost invariably assumes that the data to be analyzed are fully observed. In most practical applications this is an unrealistic assumption.…