Research
Questions, answered carefully.
What we've published, what we're working on, and what we want to find out next.
- 2026
CybersecurityUnder reviewST-GraphAD: Spatio-Temporal Graph Neural Network for Network Intrusion Detection on UNSW-NB15
Ayan Bhaumik · co-authors to be added
Neurocomputing (NEUCOM-D-26-19319)
A temporal attention mechanism for graph-based anomaly detection in network traffic, evaluated on UNSW-NB15.
- 2026
Machine LearningUnder reviewA Hybrid Machine Learning Framework for Detecting Fraudulent Online Job Postings
Ayan Bhaumik · co-authors to be added
SN Computer Science (SNCS-D-26-07666)
A comparative study of classical, ensemble and neural approaches to spotting fraudulent job postings online.
- 2026
CybersecurityUnder reviewAn Adaptive and Explainable ML Framework for Zero-Day Cyberattack Detection Under Distribution Shift
Ayan Bhaumik · co-authors to be added
Submitted for publication
Adaptive, explainable detection of previously unseen cyberattacks when real-world data drifts away from training conditions.
- 2026
Computer VisionUnder reviewA Region-Specific Benchmark of Low-Light and Haze Restoration for Downstream Detection on Indian Traffic and Surveillance Scenes
Ayan Bhaumik · co-authors to be added
Submitted for publication
A benchmark of image-restoration methods for low-light and hazy conditions, measured by how well object detection works afterwards on Indian traffic and surveillance imagery.
- 2025
Federated LearningPublishedFBCA-IoMT: A Federated Binary Framework
Ayan Bhaumik · Archita Bhattacharyya & Mrinal Kanti Deb Barma
Springer Nature, Lecture Notes in Networks and Systems, vol. 1651 (ICT4SD 2025)
A federated binary contrastive autoencoder framework for privacy-preserving anomaly detection in Internet of Medical Things (IoMT) environments.
Research agenda
What we want to find out
Privacy-preserving learning
Federated and on-device methods that keep data where it belongs.
Agents that can be trusted
Tool-using AI systems with clear limits, audit trails and human checkpoints.
Language access
Models that serve Indian languages and low-resource settings well.
Security that adapts
Intrusion and zero-day attack detection that stays reliable and explainable as real-world data shifts.
Vision for Indian conditions
Computer vision benchmarks built on local traffic, low light and haze — not just clean global datasets.
Learning science
How students actually pick up hard technical skills, and how to help.
Collaborate with us
Universities and researchers: let's work on something together.