MsSadia Sharmin
Research Postgraduate
Department of Electrical and Electronic Engineering - Faculty of Engineering
Orcid identifier0000-0002-5783-6242 (opens in a new tab)
- Research PostgraduateDepartment of Electrical and Electronic Engineering - Faculty of Engineering
- Department of Electrical & Electronic Engineering, Electrical Engineering, South Kensington Campus, United Kingdom
RESEARCH
My current research centers on anomaly detection in large-scale, high-dimensional datasets collected from sensors, communication networks, and signal processing systems. The goal is to identify unusual or rare patterns that may indicate faults, intrusions, or system degradation — crucial for industrial monitoring, cybersecurity, and IoT applications.
To tackle this, I use tensor decomposition techniques that can capture the multi-dimensional structure of complex data. These methods help uncover hidden relationships and patterns that traditional flat models often miss, making them especially useful for detecting subtle anomalies in noisy or incomplete datasets.
To tackle this, I use tensor decomposition techniques that can capture the multi-dimensional structure of complex data. These methods help uncover hidden relationships and patterns that traditional flat models often miss, making them especially useful for detecting subtle anomalies in noisy or incomplete datasets.