To empower non-programmers, Confirm’s Ivan Guevara is working on a digital platform for smart manufacturing using low-code technology.
Ivan Guevara is a PhD researcher at Confirm, the Science Foundation Ireland research centre for smart manufacturing, based at the University of Limerick.
He got interested in the possibilities of artificial intelligence while working as a software engineer in Argentina. He is now looking at how new technologies can be brought into factories for industry 4.0, but in a way that is accessible to people without a computer science background.
‘Nowadays only people with certain kind of skills can use those tools, so we are working on this platform to simplify the process’
– IVAN GUEVARA
Tell us about the research you’re currently working on.
After starting my PhD, I got the chance to work with Prof Conor Ryan and his team. They are specialised in what we call ‘evolutionary computing’, which is basically machine learning but using elements from the theory of evolution. As my PhD involves smart manufacturing (the work done within a factory but leveraged by AI, IoT devices and analytics), I started mixing both approaches in my daily research to improve the results we were working on.
Right now, I’m working on a digital platform to enable non-programmers to be able to use all these kinds of technologies, in order to democratise the software development process. Nowadays only people with certain kind of skills can use those tools, so we are working on this platform to simplify the process and try to empower them as well.
My research involves developing an analytics control board for smart manufacturing using low-code technology. We are working on this digital platform, allowing non-expert programmers to use technologies such as machine learning, blockchain, IoT interaction, web development, etc. The whole idea is to give them the tools to easily bootstrap and create a professional software development cycle.
My supervisor, Prof Tiziana Margaria, has been working on this approach for quite a long time and she proposed this project because it is not only industry-related, but also is useful for students to learn from without too much knowledge about it. Software-related tools sometimes are complex workflows, hard to understand, so this comes in handy for everyone who wants to work on these topics without too much detail.
In your opinion, why is your research important? What kind of impact do you foresee?
Technology as we knew it when we were kids has been transformed – we can barely recognise it. It has been evolving fast during the past 30 years and I think this will evolve even faster with the inclusion of disruptive technologies such as AI, analytics, big data and industry 4.0.
This situation will force us to adapt to the changing circumstances and this basically means having to learn more and more each time. With the current approach we have right now, instead of putting the focus on solving the actual problem, we tend to deal with boilerplate code from programming languages, which also are prone to errors.
Low-code technologies aims to solve this by grabbing solutions already coded, tested and used by experts, and deliver them to non-experts to solve a real-life problem. I think the possibilities we have with these kinds of technologies are infinite, as anyone with no background in computer science could actually develop a solution to a problem of any kind of magnitude.
What inspired you to become a researcher?
Probably the spark was produced when I was taking my math modules in the early stages of my computer science career. I saw the way many mathematicians changed the world with their contributions, and I thought I needed to do the same, contributing somehow to human knowledge.
I think that was what inspired me to be a researcher, the chance of making a difference. Research in general is about making contributions to humanity, having the chance to somehow make a better world and, in the context of my research, helping people to have access to complex software tools and make them available for everyone.
What are some of the biggest challenges or misconceptions you face as a researcher in your field?
I think the biggest challenge we face is the uncertainty during our careers. When you first start working on your research, you have multiple paths to follow and some of them go straight to a dead end. You need to have the ability to somehow stop, go back and find another one, but that sometimes can be tricky.
Research is like a giant unknown map and researchers are the explorers going through it, connecting dots and building the bridges between different investigations. We have the freedom to explore and connect dots from all kinds of places. But sometimes you end up connecting dots where there is no easy way out, where getting a solution is far more complicated than you expected, so we need to take small steps and be sure before assuming anything.
Do you think public engagement with science has changed in recent years?
Public engagement has definitely changed in the past few years. I think there are pros and cons about that.
We can definitely reach more people, even from another part of the world and engage with them, show them what we are doing here, and that’s something truly remarkable. Even research itself has changed, giving us the chance to work remotely and be more productive, as we have the chance to focus only on our research.
Of course there are downsides in this as we lose the chance to interact face-to-face with people, and sometimes it is difficult to measure whether they are getting the message or not, how they feel about the things we are telling them.
Definitely a face-to-face reunion has a great advantage in that aspect, but we need to find ways to deliver the message in a more efficient way, capturing the attention of people and interacting with them in a way they feel part of the talk we are giving. It’s a nice challenge we have from here, as this kind of engagement will continue to grow in the future.
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