activity
20182025
most citedDetecting and Localizing Anomalous Cliques in Inhomogeneous Networks using Egonets

8 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ME2025

Causal Inference Under Network Interference

Subhankar Bhadra, Michael Schweinberger

We review the growing body of research on the challenging topic of interference in causal inference. Interference arises when the treatment assignments of connected units affect th…

stat.ME2025

A Unified Framework for Community Detection and Model Selection in Blockmodels

Subhankar Bhadra, Minh Tang, Srijan Sengupta

Blockmodels are a foundational tool for modeling community structure in networks, with the stochastic blockmodel (SBM), degree-corrected blockmodel (DCBM), and popularity-adjusted…

physics.comp-ph2025

Regression Model for Measurement of Wound Dimensions by Webcam Scanners and Time-of-Flight Sensors

S. B. Wibowo, A. A. Nugroho, L. Awaludin +1

One use of image processing is for medical equipment such as wound identification. This technology is carried out non-invasively by taking images so as to avoid direct touch with t…

stat.ME2025

Scalable community detection in massive networks via predictive assignment

Subhankar Bhadra, Marianna Pensky, Srijan Sengupta

Massive network datasets are becoming increasingly common in scientific applications. Existing community detection methods encounter significant computational challenges for such m…

stat.ME2024

A regression framework for studying relationships among attributes under network interference

Cornelius Fritz, Michael Schweinberger, Subhankar Bhadra +1

To understand how the interconnected and interdependent world of the twenty-first century operates and make model-based predictions, joint probability models for networks and inter…

stat.ME2018★ 8 cited

Detecting and Localizing Anomalous Cliques in Inhomogeneous Networks using Egonets

Subhankar Bhadra, Srijan Sengupta

Cliques, or fully connected subgraphs, are among the most important and well-studied graph motifs in network science. We consider the problem of finding a statisti- cally anomalous…