An interview with Professor Shaun Hendy
Professor Shaun Hendy wears many hats and typically has a very busy schedule. Thankfully for us, he has made some time available to chat and answer a few questions to provide our community with a few words of advice.
Can you describe the work of the complex systems group at Callaghan Innovation, previously IRL?
The study of complex systems is an interdisciplinary field that has arisen out of biology, physics and the social sciences in the last few decades. When we talk about complex systems we don't just mean things that are complicated; complex systems consist of many interacting entities, be they atoms, plants or people, that are more than the sum of their parts. Complex systems are often described as self-organising; through the interactions between their constituent parts, they arrange themselves into surprisingly simple hierarchical patterns.
Our group is particularly interested in how innovation works. By analysing a very large database of patents, we've found patterns in the way ideas and knowledge is generated. For instance, the way intellectual property is spread amongst companies is very similar to the way biomass is distributed amongst species in an ecosystem. Using concepts from complex systems that have been developed to study ecosystems, we've started to develop an understanding of what makes some countries, regions and companies more innovative than others.
Where do you see NeSI fitting in to the science and innovation space?
Computation and simulation are becoming increasingly important in all fields of science and industry. With the advent of social media and big data, even marketing has become a computational problem – it’s not so much Mad Men as maths majors these days.
NeSI provides a computational capability to the science and innovation sector that goes beyond what the individual players in the system could achieve in isolation. By pooling computational resources and providing an infrastructure by which these resources can be accessed anywhere in the country it really has the potential to lift performance across the sector.
As a distributed resource, it is also an experiment in how we can beat distance. We know that proximity is a real driver of innovation, but proximity is something that we just don't have a lot of in New Zealand - we have the population of a medium-sized city and we are a long way from the rest of the world. NeSI has the potential to help us beat distance and work together in more innovative ways.
Do you have any recommendations how early-stage scientists up-skill themselves to add computational methods to their work?
You’ve got to get yours hands dirty, I think. Set aside time to write some code to replace a calculation that's built into your point-and-click black box package. While you don't want to reinvent the wheel, having code that replaces a repetitive manual task can boost productivity enormously. Suddenly you'll find that you can deal with data in much higher volumes – this can be a game changer.
My first paper in physical review letters came about because I suddenly had access to parallel computing and could explore the parameter space of the problem I was working on in much more detail. Parallel computing helped me strike gold!
You’ve touched upon closer human relationships as driving economic growth in larger economies. Cities tend to do very well. Is there anything that the eResearch and eScience communities can do to improve their inter-connectedness and contribute to becoming a city of 4 million people?
We’ve got to lead the way in developing, utilising and socialising virtual collaboration, data sharing and open science practices. There is no other way forward for New Zealand, short of us all moving to Sydney. If the the eResearch community doesn't do it, no one else will!
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