YANNIS SPYRIDIS
About
Yannis Spyridis is an Applied AI Researcher and Engineer with a PhD from the University of Sheffield. His work focuses on building and evaluating intelligent systems for real-world environments, with experience across multi-agent systems, reinforcement learning, and AI-enabled decision support. His work spans both academic research and applied programmes within large European and UK research projects.
Alongside research, he has strong hands-on experience in developing production-oriented AI systems, including Python backends, REST APIs, and data pipelines. His interests lie in bridging the gap between research prototypes and deployable AI systems that can operate in real-world settings. His recent work is with generative AI and LLM-based systems, with an emphasis on reliability, and agentic workflows.
He is currently working as a full-time lecturer in
Computer Science and Artificial Intelligence at
Kingston University London.
Scientific Publications
International peer-reviewed Journals
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"Intraclass Clustering-Based CNN Approach for Detection of Malignant Melanoma,"
Sensors, 2023, 23, 926,10.3390/s23020926
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"SDN-Based Resilient Smart Grid: The SDN-microSENSE Architecture,"
Digital, 2021, 1, no. 4,10.3390/digital1040013
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"Towards 6G IoT: Tracing Mobile Sensor Nodes with Deep Learning Clustering in UAV Networks,"
Sensors, 2021, 21, 3936,10.3390/s21113936
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"SPEAR SIEM: A Security Information and Event Management System for the Smart Grid,"
Computer Networks, 2021,10.1016/j.comnet.2021.108008
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"End-to-End Deep Graph Convolutional Neural Network Approach for Intentional Islanding in Power Systems Considering Load-Generation Balance,"
Sensors, 2021, 21, 1650,10.3390/s21051650
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"Modelling and simulation of a new cooperative algorithm for UAV swarm coordination in mobile RF target tracking,"
Simulation Modelling Practice and Theory, Volume 107, 2021, 102232, ISSN 1569-190X,10.1016/j.simpat.2020.102232
International peer-reviewed Conference Proceedings
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"Autonomous AI-enabled Industrial Sorting Pipeline for Advanced Textile Recycling,"
20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Abu Dhabi, United Arab Emirates, IEEE, 2024,10.23919/FRUCT61870.2024.10516405
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"Empowering Prior to Court Legal Analysis: A Transparent and Accessible Dataset for Defensive Statement Classification and Interpretation,"
35th Conference of Open Innovations Association (FRUCT), Tampere, Finland, IEEE, 2024, pp. 737–743,10.23919/FRUCT61870.2024.10516405
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"Variational Quantum Approach for the Multiple Traveling Salesman Problem Optimisation,"
19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Paphos, Cyprus, IEEE, 2023, pp. 354–358,10.1109/DCOSS-IoT58021.2023.00064
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"An AI-Assisted Skincare Routine Recommendation System in XR,"
7th International Conference on Artificial Intelligence and Virtual Reality (AIVR 2023), Kumamoto, Japan, Springer, 2023,10.48550/arXiv.2403.13466
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"A Robust Deep Learning Architecture for FireFighter PPEs Detection,"
2022 IEEE 8th World Forum on Internet of Things (WF-IoT), Yokohama, Japan, 2022, pp. 1–6,10.1109/WF-IoT54382.2022.10152263
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"Augmented reality training, command and control framework for first responders,"
7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), Ioannina, Greece, 2022, pp. 1–5,10.1109/SEEDA-CECNSM57760.2022.9932966
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"An Augmented Reality Framework for First Responders: the RESPOND-A project approach,"
Panhellenic Conference on Electronics & Telecommunications (PACET), Tripolis, Greece, 2022, pp. 1–6,10.1109/PACET56979.2022.9976376
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"Intentional Islanding of Power Systems Through Self-Embedding Learning,"
IEEE Globecom Workshops (GC Wkshps), 2021, pp. 1–6,10.1109/GCWkshps52748.2021.9682069
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"Synthetic Traffic Signs Dataset for Traffic Sign Detection & Recognition In Distributed Smart Systems,"
17th International Conference on Distributed Computing in Sensor Systems (DCOSS), 2021, pp. 302–308,10.1109/DCOSS52077.2021.00056
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"Gamified First Responder Training Solution in Virtual Reality,"
17th International Conference on Distributed Computing in Sensor Systems (DCOSS), 2021, pp. 295–301,10.1109/DCOSS52077.2021.00055
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"Increasing resilience of power systems using intentional islanding; a comparison of Binary genetic algorithm and deep learning based methods,"
IEEE International Conference on Cyber Security and Resilience (CSR), 2021, pp. 491–496,10.1109/CSR51186.2021.9527918
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"Rule-based Autonomous Tracking of RF Transmitter Using a UAV Swarm,"
12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), Porto, Portugal, 2020, pp. 1–3,10.1109/CSNDSP49049.2020.9249591
Research Projects
SPEAR: Secure and private smart grid
The project designed privacy-preserving and secure AI-driven data infrastructures for next-generation smart energy grids.
SDN: Microgrid resilient electrical energy system
The project developed resilient microgrid control and monitoring systems, including AI-supported mechanisms for reliable local energy networks.
RESPOND-A: Next-generation equipment tools and mission-critical strategies for first responders
The project developed AI-enabled decision support and situational awareness tools for emergency response operations.
RAIDO: Reliable AI and data optimisation
The project aims to deliver reliable AI optimisation pipelines for forecasting, data enrichment, and decision-making towards green AI.