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Dr Peter Rockett is an Honorary Lecturer at the School of Electrical and Electronic Engineering, University of Sheffield. He holds a PhD in Semiconductor Physics from the University of Manchester (1980) and has been affiliated with the University of Sheffield since 1990. His research focuses on physics-informed genetic programming, machine learning for engineering, and evolutionary algorithms applied to feature extraction, control systems, and computer vision.
Key areas of expertise include multiobjective genetic programming, algorithm optimization, and model-predictive control for non-domestic buildings. He has contributed to the development of standardized genetic programming frameworks (e.g., GPML) and has explored applications in robotics, cybersecurity, and image processing. His work bridges theoretical foundations with practical engineering challenges, emphasizing cross-domain feature extraction and algorithmic innovation.
Recent publications highlight advancements in pruning genetic programming trees using permutation tests, energy-efficient building control systems, and semantic-based local search methods. Rockett has collaborated extensively with researchers globally, producing influential papers in journals like Evolutionary Intelligence, Genetic Programming and Evolvable Machines, and IEEE Transactions on Evolutionary Computation.
No scientific awards are explicitly listed, but his extensive publication record underscores sustained academic contributions. His advising and mentoring focus on PhD and Master’s students in machine learning and engineering informatics, with research teams often collaborating on interdisciplinary projects involving control systems and AI-driven solutions.
