Mr James Barrett

Qualifications:

PhD, MSc, BSc, FdSc, AfCIIS (pending renewal)

Position:

Lecturer in Data Science

Department:

Faculty of Environment and Technology (FET)

About me

I am a Data Science Lecturer and active researcher within the Department of Computer Science and Creative Technologies at the University of the West of England (UWE Bristol). My work bridges the gap between academic theory and real-world industrial application, focusing heavily on cutting-edge Machine Learning (ML) technologies and Explainable AI (XAI). Having completed my PhD at UWE Bristol specializing in Cybersecurity Telecommunication Analytics and Machine Learning, my academic journey is deeply rooted in this institution, where I also serve as a postgraduate researcher investigating solutions to complex industry challenges.

My research portfolio is primarily centered on enhancing the interpretability and usability of advanced AI systems within highly sensitive, large-scale networks. I specialize in applying ML and analyst-driven XAI methodologies to time-series forecasting and cybersecurity analytics, ensuring that complex algorithmic decisions can be effectively understood and utilized by domain experts. My published research includes studies on identifying threats to security and service in mobile networks and utilizing call detail records for advanced data analytics, establishing robust frameworks for predictive maintenance and digital forensics.

Alongside my academic responsibilities, I maintain a strong footing in industry-focused advisory and consultation roles. I work closely with leading organizations to deploy predictive ML frameworks, including ongoing consultancy for the Accelerated Capability Environment (ACE) in government policy research, and collaborative research and development contracts with global telecom partners like Ribbon Communications. This dual engagement ensures my research remains closely tied to emerging threat landscapes, engineering standards, and production-level system architectures.

As an educator, I am dedicated to preparing the next generation of computer science and data analytics professionals. Leveraging my extensive background across data science, cybersecurity forensics, and software engineering, I deliver comprehensive, industry-relevant instruction that emphasizes both theoretical rigor and practical execution. I aim to foster an environment of continuous learning where students are equipped with the technical proficiency and critical problem-solving skills necessary to navigate the rapidly evolving artificial intelligence landscape.

Area of expertise

Python, Machine Learning, Computer Technology, Time Series Forecasting, Cybersecurity, Systems Analysis

Publications

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