About me

My face

Software Engineer for MeerTRAP,
The University of Manchester.
Using code to try to find fast radio
transients.

I am mainly interested in the use of High Performance Computing (mainly GPUs) in radio transient searches (Pulsars, RRATs, FRBs and whatever comes next…). I am also interested in building responsive GUI and web-based applications (Python/C++ Qt, JavaScript and all the required frameworks) to enable researchers quick, hassle-free and informative access to their data.

Things I usually do

C++: GPU programming with CUDA, multithreaded programming, bitwise operations and tricks, Qt

JS: Vue, NodeJS, ExpressJS, plotting, SQL databases

Outreach: IOP Computational Physics Group, GPU Hackathons mentoring, Citizen Science Projects

Python: CuPy, async programming, plotting, TensorFlow, PyQT, real-time processing, fighting indentation

Docker and Singularity: build and runtime optimisations, best practices, containerising everything

Misc: Linux, bit of Unity, some actual physics and maths, using Fourier Transforms a bit too much

Past Experience

Software Sustainability Institute 2021 Fellow
(May 2021 – now)
As part of this Fellowship I will be organising workshops, training and drop-in sessions for scientists interested in using containers for their reproducible research. The main focus will be Docker and Singularity technologies.

Institute of Physics Computational Physics Group Committee Member
(2020 – now)
As the Committee Member I am responsible for producing the yearly Group Newsletter. I am also introducing a new series of regular events that create an environment for the Group Members to share their work and foster new collaborations.

Software Engineer for MeerTRAP project / The University of Manchester
(2018 – now)
I am developing and maintaining parts of the processing and post-processing pipelines using C++ and Python accelerated with GPUs. I am mainly involved in the development of the post-processing stages of the candidate transients. This is achieved with the help of a highly-optimised GPU-aware pipeline responsible for producing the final detection products and running ML classification.

PhD Astronomy and Astrophysics / The University of Manchester
(2014 – 2018)

Thesis title: Exploring the dynamic radio sky with many-core high-performance computing

I was looking into the use of High Performance Computing, with the focus on GPU computing in the pulsar and radio transient searches. I am mainly interested in single pulse detection techniques and the influence of the interstellar and intergalactic medium on the properties of the electromagnetic radiation.

Summer Intern / Space Telescope Science Institute
(June 2013 – August 2013)
I was working on porting and profiling portions of the data processing pipeline used, for example, by the Hubble Space Telescope to Intel Xeon Phi accelerators.