Dr Nick Brown

I am a research fellow in EPCC at the University of Edinburgh, and have interests in High Performance Computing (HPC) and data science. Working at the UK’s leading supercomputing centre, much of my work has centred around enabling some of the most powerful machines in the world to most effectively provide scientific insights. This has taken a variety of forms, for instance working with the Met Office on developing the MONC atmospheric model, to exploring parallel programming abstractions and technologies. I am also very interested in the role of novel architectures as future hardware for high performance workloads, including reconfigurable architectures and micro-cores. For the later I developed ePython, which is the world’s smallest implementation of Python and designed to provide programmer productivity and performance on micro-core technologies.

I have been involved in and led a number of data projects, including some focused around machine learning especially in the oil and gas sector. I lead a work package on VESTEC, which is an EU funded FET research project, exploring the fusion of real-time data and HPC for urgent computing. I am also involved in teaching, being the course organiser for Parallel Design Patterns which is a postgraduate taught MSc module, primary supervisor of two PhD students, and supervise a number of MSc students each year.

Before joining EPCC in 2012 I worked in industry at BAE Systems. Prior to that I obtained my PhD in computer science at the University of Durham, exploring novel programming abstractions via the type system for writing high performance parallel codes.