Ioannis Mavromatis

About me:

I am a Lead Research Engineer at Digital Catapult with over a decade of experience designing and delivering large-scale, autonomous and distributed systems across the cloud–edge continuum. My work sits at the intersection of platform engineering, Machine Learning, and Cloud-native technologies, with a strong focus on building robust platforms that move from research prototypes to production-grade deployments.

Currently, I lead the technical development and platform delivery of large-scale AI-enabled R&D platforms, and act as a tech leader in a number of projects (e.g., REASON, SUSTAINET-guarDian, CHEDDAR CHEESE and more). I explore emergent systems and solutions targeted around cloud-edge computing deployments and how autonomy can enable platform self-configuration, how Cloud Native architectures can enhance the disaggregation, decentralisation and distributed computation within such systems, and how we can harness Generative AI capabilities across MLOps and DevOps pipelines.

My core expertise is in platform and ML systems for large-scale environments. I work extensively on AI-assisted automation, distributed and federated ML pipelines, and energy-aware AI workflows deployed across cloud and edge infrastructures. More recently, I have been focusing on Retrieval-Augmented Generation (RAG), Agentic AI, and LLM-powered platform tooling, developing intelligent agents that assist with deployment reasoning, capability matching, telemetry analysis, and automated configuration generation for cloud-native systems.

In previous roles, I architected secure IoT and edge-cloud platforms, developed federated drift detection frameworks, and led research activities around scalable AI and optimisation in distributed environments. I was also the solution architect and main developer of the award-winning UMBRELLA platform, delivering a real-world, city-scale IoT backend supporting secure, scalable, and data-driven services.

Overall, I enjoy building end-to-end platforms that operate at scale — from system design and research to validation in large, distributed deployments. I am particularly interested in systems that combine cloud-native infrastructure, AI/ML, and intelligent automation to improve scalability, efficiency, and operational resilience.

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Research Interests:

My research interests focus on Distributed Systems and the Cloud–Edge Continuum, with an emphasis on intelligent, scalable, and production-ready platforms. Key areas include:

• Cloud-native platforms and large-scale distributed system design
• Cloud–edge orchestration and cross-domain automation
• Agentic AI, LLMs, and RAG systems for platform engineering
• Federated and distributed machine learning
• Sustainable and energy-efficient AI deployments (Green MLOps)
• Observability, validation, and self-healing infrastructure

I have consistently worked on real-world, large-scale deployments involving multi-cluster Kubernetes infrastructures, edge–cloud platforms, and data-intensive distributed systems. My past work also spans IoT platforms, Digital Twins, autonomous systems, and secure cyber-physical infrastructures, always with a strong emphasis on scalability, automation, and operational robustness.

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Open-source Projects:

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Previous positions:

• Principal Research Engineer at Toshiba Europe Ltd.
• Research Associate at the University of Bristol
• Research Assistant at the University of Bristol

I also hold a “PhD in Vehicular Communications” from the University of Bristol, UK, where I worked with Prof Robert Piechocki and Dr Andrea Tassi. Before that, I got an “MSc in Wireless Communications and Signal Processing” from the University of Bristol, UK, and a “BSc in Computer Science” from Alexander Technological Institute of Thessaloniki, Greece, currently called International Hellenic University.