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Chijiuka Akuma
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PhD research at Leeds Beckett University focused on AI-driven solutions for Intelligent Transport Systems, with a broader interest spanning Machine Learning, Computer Vision, Blockchain, and LLMs.
Current PhD
Leeds Beckett University
Investigating privacy-preserving, decentralised learning architectures for object detection in mixed road user environments. Research spans YOLOv8 federated training strategies, convergence behaviour analysis, and comparative evaluation of centralised vs. federated approaches, building toward safer, more intelligent autonomous transport.
Privacy-preserving distributed machine learning without centralising sensitive data.
Federated YOLOv8 object detection for mixed road users — privacy-preserving AI for safer transport.
Autonomous agents that collaborate and communicate to solve complex real-world problems.
Deep learning, predictive analytics, SARIMAX forecasting, and statistical modelling.
Designing AI systems that augment human capability and prioritise user needs and ethics.
Real-time YOLOv8 object detection for autonomous and intelligent systems.
Statistical modelling, machine learning, and data visualisation for insight generation.
Academic credential verification and trust frameworks for educational systems.
Akal University, Punjab, India
3–5 April 2026
Amity University, Noida, India
18–19 September 2025
4 peer-reviewed journals and 4 international conference papers across AI, Blockchain, Data Science, and Transport.
View All Publications →