Rate My Professor Edmund Sadgrove

Dr. Edmund Sadgrove serves as Lecturer in Computer Science within the School of Science and Technology at the University of New England. He earned his Bachelor of Computer Science (Honours) and PhD from the same institution. Before pursuing higher education, Sadgrove completed an apprenticeship in the electronics trade, working as a service engineer. His doctoral research was conducted as part of the precision agriculture research group at the University of New England, where he developed expertise in applying computational methods to agricultural challenges. Currently, he contributes to ongoing projects in this domain while teaching core computing units.

Sadgrove's research centers on artificial intelligence, machine learning, data mining, data structures, and computer vision algorithms for robotics, with a primary focus on machine learning solutions in agriculture. He investigates artificial neural network-based methods, such as colour feature extreme learning machines and support vector machines, for detecting objects in crops and pastoral landscapes. His scholarly output includes key publications like 'Real-time object detection in agricultural/remote environments using the multiple-expert colour feature extreme learning machine (MEC-ELM)' in Computers in Industry (2018), 'Fast object detection in pastoral landscapes using a Colour Feature Extreme Learning Machine' in Computers and Electronics in Agriculture (2017), 'Developing an extreme learning machine based approach to weed segmentation in pastures' in Smart Agricultural Technology (2023), and 'Joint plant-spraypoint detector with ConvNeXt modules and HistMatch normalization' in Precision Agriculture (2025). Additional contributions encompass works on camera trapping technology, AI chatbot adoption, and software-defined networks. Sadgrove teaches databases, introductory programming, advanced web programming, reinforcement learning, and fundamentals of cybersecurity and privacy. He also coordinates courses such as the Graduate Certificate in Artificial Intelligence and Master of Data Science. His research has garnered over 160 citations, advancing precision agriculture and computational applications in environmental monitoring.