C. James Taylor

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Professor of Control Engineering

University of Lancaster

United Kingdom

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About

Professor C. James Taylor is a faculty member at Lancaster University, located in the United Kingdom. His research areas encompass control engineering, remote radiation characterization, energy-resolved photon responses, and the application of machine learning in predicting power outputs and analyzing electricity theft. Recent publications include studies on collimators for radiation tasks and hyperspectral imaging for fission product quantification.

Recent Grants

Grant: Close

Autonomous Inspection for Responsive and Sustainable Nuclear Fuel Manufacture (AIRS-NFM)

Open Date: 2021-09-05

Close Date: 2024-09-04

Grant: Close

Novel High Performance Wave Energy Converters with advanced control, reliability and survivability systems through machine-learning forecasting

Open Date: 2021-04-05

Close Date: 2024-04-04

Grant: Close

Advancing Location Accuracy via Collimated Nuclear Assay for Decommissioning Robotic Applications (ALACANDRA)

Open Date: 2021-03-01

Close Date: 2025-02-28

Grant: Close

National Centre for Nuclear Robotics (NCNR)

Open Date: 2017-10-01

Close Date: 2021-03-31

Grant: Close

Technology development to evaluate dose rate distribution in PCV and to search for fuel debris submerged in water

Open Date: 2015-11-01

Close Date: 2018-03-30

Articles (17)

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2025

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2024

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2021

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2020

Collaborators (18)

Allahyar Montazeri

University of Lancaster

UNITED KINGDOM

C. James Taylor

Research Interests

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About

Recent Grants

Articles (17)

Low-density collimators for remote radiation characterisation tasks

Improving radiation localization via energy-resolved angular photon responses

Hyperspectral imaging suggests potential for rapid quantification of fission products in spent nuclear fuel

Data-Driven Insights: Boosting Algorithms to Uncover Electricity Theft Patterns in AMI

Enrichment measurement by passive γ-ray spectrometry of uranium dioxide fuel pellets using a europium-doped, strontium iodide scintillator

TALOS Wave Energy Converter Power Output Prediction Analysis Based on a Machine Learning Approach

Robust Data Driven Analysis for Electricity Theft Attack-Resilient Power Grid

Localising and identifying radionuclides via energy-resolved angular photon responses

Improved localization of radioactivity with a normalized sinc transform

Time-Domain Implementation and Analyses of Multi-Motion Modes of Floating Structures

Hydrodynamic studies of floating structures

A Stacked Machine and Deep Learning-based Approach for Analysing Electricity Theft in Smart Grids

A Low-Cost and Semi-Autonomous Robotic Scanning System for Characterising Radiological Waste

Radiation testing of low cost, commercial off the shelf microcontroller board

Implementation and Evaluation of a Semi-Autonomous Hydraulic Dual Manipulator for Cutting Pipework in Radiologically Active Environments

Adaptive treatment and robust control

Plant leaf position estimation with computer vision

Collaborators (18)

Allahyar Montazeri

Robert Dorrell

Andrew Parker

David Cheneler

W Sheng

colin boxall

Barry Lennox

Andrew Kennedy

Andrew West

Malcolm Joyce

Manuel Bandala

Ioannis Tsitsimpelis

Xiandong Ma

Jaime Zabalza

Stephen David Monk

George Aggidis

Emma Wilson

Stephen Marshall

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