Electronic engineering & medical imaging

Subramaniam
Murugesan.

PhD Researcher
Research Technician, Blizard Institute

Queen Mary University of London

London, United Kingdom

About me

I work on RF localisation and machine learning for wireless capsule endoscopy.

At Queen Mary, my PhD investigates how radio measurements can tell us where a capsule is. At the Blizard Institute, I contribute to CE-Track through clinical imaging reconstruction and anatomical modelling.

Email ↗Google Scholar ↗GitHub ↗LinkedIn ↗Curriculum vitae ↗

Education

2024–present
PhD, Electronic Engineering
Queen Mary University of London
2022–2023 · Distinction
MSc, Big Data Science
Queen Mary University of London
Bachelor of Technology
Bioinformatics
SASTRA Deemed University, India

Education & appointments →

CE-Track

Research Technician
Blizard Institute
May 2026–present

Working with Professor Akram Alomainy, Dr Mohamed Adhnan Thaha and Dr Muhammad Qamar Satti.

Our research →

What I work on

Research interests

Overview ↗

Choose a research areaCapsule localisationColon modellingE-health systems

PhD · Electronic Engineering

Where is the capsule?

My doctoral research investigates RF localisation for wireless capsule endoscopy. I use radio measurements and antenna geometry to estimate capsule position, with conditional flow matching as a probabilistic approach.

My first-author paper: anchor-aware conditional flow matching, EuCAP 2026.

Read about my RF research

RF capsule localisation with body-worn anchors, a cylindrical model and a learned conditional flow — EuCAP paper figure · Murugesan et al.

Conceptual illustration from our EuCAP paper, linking wearable anchors with the learned conditional flow.

CE-Track · Blizard Institute

How can we describe colon shape?

As a Research Technician, I contribute to AI-based reconstruction and modelling of clinical imaging data. My Colon-Roadmap work explores how CT colonography could support a model of gastrointestinal anatomy.

Current stage: study design and development. This diagram describes the planned workflow.

Explore the project and collaborators

Planned Colon-Roadmap workflow from historical CT colonography to model development and independent anatomical evaluation. — My Colon-Roadmap study plan · conceptual workflow

An original schematic from my research project. It shows a study plan, not completed experiments.

First-author paper · IEEE JBHI, 2024

How do we serve an image-prediction model?

My earlier e-health work brought neural networks and serverless computing together for tuberculosis prediction. The architecture uses Amazon EKS and AWS Fargate to serve prediction requests.

Connection to my wider work: machine learning methods and the computing systems that support them.

Read about the e-health work