PhD in Electronic Engineering
Queen Mary University of London
London, United Kingdom
RF localisation and machine learning for wireless capsule endoscopy.
Curriculum vitae
Subramaniam Subramanian Murugesan · London, United Kingdom
Appointments
2024–present
PhD Researcher
Queen Mary University of London · School of Electronic Engineering and Computer Science
EPSRC DTP funded research in RF localisation and machine learning for wireless capsule endoscopy.
May 2026–present
Research Technician
Blizard Institute · Queen Mary University of London
Research Technician for CE-Track, contributing AI-based approaches to clinical imaging reconstruction and anatomical modelling.
Education
MSc in Big Data Science
Queen Mary University of London
London, United Kingdom
Distinction.
Bachelor of Technology in Bioinformatics
Thanjavur, India
Research supervision
My doctoral research is supported by an EPSRC studentship in the Antennas and Electromagnetics Research Group.
Supervisors: Professor Akram Alomainy and Dr Mohamed Adhnan Thaha.
Methods and tools
- Programming
- Python, SQL
- Machine learning
- PyTorch, TensorFlow
- RF engineering
- Software-defined radio, Antenna design
- Cloud and web
- AWS Lambda, EC2 and RDS, Django, Flask
Publications
Publication details- Machine Learning-Based Anchor-Aware Conditional Flow Matching for RF Localization in Wireless Capsule Endoscopy
20th European Conference on Antennas and Propagation (EuCAP), pp. 1–5 · 2026
- Agentic AI: Vision and challenges
PLOS Complex Systems, 3(8), e0000120 · 2026
- Edge AI: A taxonomy, systematic review and future directions
Cluster Computing, 28, article 18 · 2025
- GAIKube: Generative AI-Based Proactive Kubernetes Container Orchestration Framework for Heterogeneous Edge Computing
IEEE Transactions on Cognitive Communications and Networking, 11(2), pp. 933–945 · 2025
- CloudAIBus: A testbed for AI based cloud computing environments
Cluster Computing, 27, pp. 11953–11981 · 2024
- Neural Networks Based Smart E-Health Application for the Prediction of Tuberculosis Using Serverless Computing
IEEE Journal of Biomedical and Health Informatics, 28(9), pp. 5043–5054 · 2024
Teaching
Lab demonstrator
Queen Mary University of London · September 2024–November 2025
Semi-Structured Data Engineering, Communication Systems, Security Engineering and Data Mining.
Teaching detailsCE-Track collaboration
Research Technician at the Blizard Institute, contributing to clinical imaging reconstruction and anatomical modelling for CE-Track.
Working with Professor Akram Alomainy, Dr Mohamed Adhnan Thaha and Dr Muhammad Qamar Satti.
LIHE MedTech Venture Builder 2025–2026 cohort
CE-Track researchProfessional development
EME Hub Summer School, Glasgow
27–31 July 2026 · Participant
ML for RF: Building Resilient Autonomy in the Electromagnetic Environment
Conferences
EuCAP 2026, Dublin
19–24 April 2026 · The Convention Centre Dublin
Attended EuCAP 2026. Our anchor-aware conditional flow matching paper was included in the conference programme.
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