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Alan Reynolds is a Lecturer with a rich research background combining computer science and mathematical physics. His early contributions in computer science primarily centered on the application of metaheuristic optimization algorithms to tackle complex industry problems. He has since expanded his research focus to include multi-objective optimization, with significant applications in data mining and machine learning. Recently, his work has explored the application of multi-objective optimization in the discovery of quantum circuits. His interests in mathematical physics encompass holographic chaos and complexity within the framework of AdS/CFT, a focus that has led to a substantial number of publications emerging from his recent PhD work.
Department of Physics research themes include Astrophysics, Materials and Devices, Particle Physics, and Quantum and Soft Matter.