Darren is a highly experienced researcher within high performance machine learning, data science and optimisation, specialising in evolutionary or population based approaches. Darren spent ten years at QinetiQ whereby he achieved considerable success in designing bespoke machine learning, data mining and optimisation algorithms applied to a variety of highly complex problem domains such as radar optimisation, mission planning and cyber defense.

Darren has developed an expertise in multi-core parallel architectures, both CPU and GPU, applying this technology to machine learning and data science algorithms for significant performance gains. Indeed, Darren was the first to port Genetic Programming onto a multi-core graphics card. More recently, Darren has demonstrated that multi-core CPUs can match graphics cards for certain tasks by improving the performance of Genetic Programming by up to 420x on a CPU. Darren has also significantly improved the computational performance of Genetic Programming on a GPU. He has also applied his expertise in exploiting parallel hardware for the purposes of high performance machine learning to other techniques such as ACO and clustering algorithms.

Darren is using his expertise in exploiting parallel multi-core hardware for the purposes of machine learning, data science and optimisation algorithms to improve performance in terms of both accuracy and timeliness. This enables improved solutions to be obtained and greater insights into large datasets that previously could only be obtained by using high-end supercomputers. Darren is also exploring combining efficiencies with the exploitation of parallel multi-core hardware for optimal performance including reducing energy consumption. This will enable high performance machine learning algorithms to be run on low power devices such as phones and tablets.

Darren is also a Chartered Engineer and Chartered Information Technology Professional with the British Computer Society (CEng MBCS CITP)

Specialties: Machine Learning, Optimisation, Parallel Processing, Multi-core Technology, Data Mining, Social Network Analysis, Evolutionary Algorithms, CUDA, Cg, Visual C++