Prof Martin Hayes from UL on his research into systems theory, why ‘pi-shaped’ graduates are the future of engineering, and the importance of perseverance.
Professor Martin Hayes is a professor of digital technology at the University of Limerick (UL) who describes his research as sitting “between the theoretical area of machine learning and AI”.
Hayes’ research looks at how to manage system resources intelligently when they are subject to uncertainty or mixed messages presented by communication channels, sensors or human operators. A large part of his work focuses on the “robust” operation of AI in critical security areas.
“How do we choose the right settings when the results of an AI system feed into human decision-making, without getting that wrong?” Hayes asked.
“Life is an obvious place where such solutions must be correct 100pc of the time.
“Some have real consequences in terms of side effects – so I’m asking how we can ensure a health system that will take advantage of AI while serving every citizen at all times.”
Hayes tells SiliconRepublic.com that as AI and machine learning technologies move from research labs to critical, high-level settings, these systems “can’t just be relatively accurate”, and that understanding how they’re built at basic levels of robustness allows the technology to be used responsibly in regulated domains like digital life.
“Professionals working in the health system, be it medicine, engineers or managers, need to understand not only how to use AI tools, but how to trust, investigate, interpret and manage them properly,” he said. “Without those foundations, discovery is hampered by over-vigilance or accelerated without the safeguards required by security-critical settings.
“Translational research that provides a foundation for those already working or wishing to participate in the European Health Data Space is at the core of my work.”
‘Pi-shaped stems’
With his work ranging from systems theory to engineering and real-world environments where these tools are used, Hayes says the interdisciplinary research environment is actually the most rewarding part of the job.
In particular, he enjoys the collaborative side of it where he works directly with industrial partners, practitioners and SMEs to “understand what the real skills gaps are and translate that into education and research that really closes”.
However, according to Hayes the most satisfying part of the job is seeing graduates continue to responsibly deploy this understanding and thinking in the workplace.
“I strongly believe that the future of engineering education is focused on the development of such ‘pi-shaped’ students who have the basic skills in data engineering enabled by AI but who have the complementary health skills needed to be able to implement those solutions in a safe, human-centered way,” he said.
Hayes has worn and continues to wear many hats at UL, where he has worked since 1997.
He is the academic leader of the UL@Work Human Capital Initiative project, which aims to develop digital, industry 4.0 talent through flexible, innovative, technology-enabled, and experiential learning. Hayes says his involvement in the UL@Work project has been “very insightful”.
“One of the key takeaways is that universities need to work together and collaborative initiatives like Digital Europe are essential in helping institutions pool their resources to provide students with an education tailored to their needs.”
Hayes also collaborates with various European universities as the principal investigator of many Digital Europe projects – such as that of Sustainable Healthcare with Digital Health Data Competence (SUSA).
SUSA is a €12.4m Digital Europe funded project led by the University of Oulu in Finland that aims to close the digital skills gap in European healthcare and support the ambitions of the EU Digital Decade and the European Health Data Space.
The project aims to deliver advanced bachelor’s, master’s and lifelong learning modules, built around SUSA’s 20 shared learning objectives benchmarked against frameworks such as the WHO Digital Health Competence Framework.
Hayes is SUSA’s UL principal investigator, leading the ‘Workpackage’, which coordinates and designs SUSA’s activities to maximize impact.
“We are leading two specific tasks: investigating how we can deliver better education through the best use of digital technologies in health – especially XR/AR and digital twin technologies – and designing a SUSA employer framework that connects students with industry in the most effective way,” he explains.
“UL’s contribution to the SUSA digital ecosystem builds on existing UL@Work advisory board models and Skillnet partnerships to keep the curriculum relevant to current workplace needs.”
Basics and patience
As someone who works in such a future-oriented research field, we asked Hayes what advice he might have for someone considering a career like his.
The first thing on the list? “Build a solid foundation on the basics,” he said.
Basically, you mean programming theory, mathematics and statistics.
“This is what allows you to adapt, optimize and ultimately deploy solutions as technology evolves,” he explains.
Next, he advises newcomers to seek interdisciplinary collaboration early on and “not be afraid to work at the boundary between engineering and the domains where it is used, whether it is healthcare, manufacturing or elsewhere”.
“Get involved in industry-facing projects where you can; the most consistent feedback we get from our students is that they’ve always enjoyed being exposed to real-world challenges through UL’s co-op education program or the in-house projects they completed during their studies,” added Hayes.
“Ultimately this sharpens the R&D questions you ask and makes you a more valuable resource,” he says.
“Finally, be patient. Your work, as a reliable AI system, is built over time and will inevitably require you to manage many uncertain situations.
“Accepting that challenge will give you the confidence to achieve your goals. Repetition builds skill!”
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