Nicholas Pritchard

A picture of Nic at ICRAR


If you're here, you probably know what you're looking for already, and I hope you find it. If you've managed to stumble here on a chance encounter, I hope you find something interesting. I am Nic, a PhD candidate researching neuromorphic computing at the International Centre for Radio Astronomy Research (ICRAR). I work on brining the next generation of neural networks to life to help clear noise from radio telescopes. I have previously worked on the execution framework for the Square Kilometre Array (SKA).

I believe technology can and should help people make the most of their time, a goal that impacts every part of my work. Let's find inventive solutions to impossible problems and a few good things to read along the way.

What am I up to now?

You will probably find me at the International Centre for Radio Astronomy Research (ICRAR), by day, and plotting my next diabolical scheme by night.

I also run a small Todo-list app called Mondage. After drowning myself in too many tasks, I wanted to be able to express that Task A needs to happen before Task B, without any sort of convoluted sub-lists. No Todo-list app I could find did this simply, so I made my own. Feel free to try it and let me know what you think.

Research Interests

Artificial Intelligence

Investigating intelligence and how it can help us tackle grand challenges is very enticing. There is enough momentum in the development of AI to worry about the safety and widespread ramifications of decision-making systems. I am particularly interested in computational neuroscience, neuromorphic computing and spiking neural networks.

Data-Intensive Astronomy

Science's data processing needs are growing immensely, and computational workflows aim to address these needs. ICRAR's Data-Intensive Astronomy team is building the computational backend for the SKA, which needs to handle a data-ingest rate up to 50TB/s. We're up for the challenge.

Scientific Reproducibility

The scientific method has given humanity some of its greatest successes and our most terrifying inventions. Continuing to do science we can trust is an eternal struggle made harder in a sea of data. Creating technologies to simplify this process is key to solving our most pressing challenges.

Quantum Computing

I so dearly hope that quantum computing one day comes to fruition, and when it does, we'll need a lot of software. My earliest work involved simulating quantum algorithms (Quantum Approximate Optimisation Algorithm (QAOA)) assuming that this technology is ready to search for problems that would benefit from these exotic machines.

Traffic and Urban Planning

Impending autonomous driving technology has ignited questions about the limits of our transport systems. I have helped the Planning and Transport Research Centre PATREC with computer vision and modelling projects to investigate autonomous technologies applied to Perth, Western Australia, my hometown.


You can find my publications on Google Scholar.


I am always on the hunt for better things to read, and for the last few years, I have kept track of my favourite book I read that year. If you find something you ultimately enjoy, let me know, and if you have some suggestions, I would love to hear them.

2023 - How the World Really Works - Vaclav Smil

An accessible but far-reaching look into the world around us.

2022 - Klara and the Sun - Kazuo Ishiguro

A touching tale from an unforgettable narrator. This story touches on what it means to love in a plausible but concerning future.

2021 - Bullsh*t Jobs - David Graeber

This snarky and entertaining take on modern work is good food for thought when looking for a place to dedicate one's efforts.

2020 - Shoe Dog - Phil Knight

2020 was a challenging year and this was the right dose of inspiring I needed to see hope for the future.

2019 - IQ84 - Haruki Murakami

In a year where I did some travelling, this book kept me company throughout my journeys. It is alarmingly original and immaculately written if you give the book patience.

2018 - The Odyssey - Homer (translation by Stephen Mitchell)

An eternal classic that stands the test of time and provides a window to antiquity.

2017 - IT - Stephen King

A story told over two eras with the same characters in a vast, albeit long, narrative. King uses horror to explore childhood trauma and the experience of passing time. There is a good reason it is still adapted to film today; it's thoroughly entertaining.

2016 - Renault - Saint Loup

From a time where the now mainstream automobile was cutting edge, Louis Renault's biography is a fascinating tale of an at times loved and at others hated industrial titan. I found this book randomly scanning through engineering texts at my University's library; I incidentally also drive a Renault.