Tell us a little bit about yourself and your current role: 

I lead a generative AI research team at Yahoo, where we build AI systems that operate at genuine scale across media and advertising platforms. But the role I find most meaningful right now is the one that sits alongside that — working with a select group of AI startups that I believe are building things that matter. Two in particular are close to my heart. Alvio Labs is rethinking how enterprises connect to their own knowledge and data, which I think is one of the most underestimated problems in the industry right now. And ONEMEDIS is bringing intelligent automation into healthcare, an area that is long overdue for transformation. I also lecture at University College Dublin, because I believe strongly that the people leading organisations today need to understand what AI actually is, not the hype, but the reality. These things are connected for me. They are all part of the same conviction that AI is not a future technology. It is already reshaping how we work, how we make decisions, and how we understand the world around us.

What path led you to where you are today?

It started with a genuine fascination with intelligence itself, how machines can learn, reason, and generate meaning from data. I came to Ireland in 2018 to pursue that seriously, and my research at TUS, funded through a collaboration with Ericsson, placed me at the frontier of applied AI during a pivotal moment. I was contributing to 5G infrastructure deployments across Europe alongside IBM and Nokia at the exact time the foundations of modern AI were being laid. That context mattered enormously. I was not studying AI in the abstract, I was watching it become infrastructure. From there, Mastercard gave me the opportunity to see how AI transforms financial decision-making at global scale. Yahoo gave me the opportunity to lead it. And what I saw across all of those experiences was the same thing: organisations sitting on extraordinary amounts of knowledge and data, with very little ability to actually use it intelligently. That observation is what drives the work I do now.

What do you love most about the work you do?

I think we are living through one of the most consequential technological transitions in human history. AI is not simply automating tasks, it is beginning to augment how humans think, diagnose, create, and decide. Being at the centre of that, working on systems that are part of that transition, is a profound privilege. What I love most is that the problems are genuinely hard and genuinely matter. In healthcare, AI has the potential to give clinicians back the time and clarity they need to focus on patients rather than paperwork. In enterprise, it has the potential to unlock institutional knowledge that currently dies when people leave organisations. These are not incremental improvements. They are structural changes to how human knowledge works. That is what gets me up in the morning.

When you're not working, where would we find you?

At home in Athlone with my family. I have a young child and that relationship with time, the way it sharpens your sense of what actually matters, is something I value deeply. Beyond that, I read constantly. A great deal of it is research, because the field moves fast enough that staying current is itself a discipline. But I also read broadly, across philosophy, economics, history of science, because understanding where AI is going requires understanding where human progress has come from. The two are not separate for me.

Looking back, how did your time at TUS influence your career or outlook?

TUS placed me in an environment where research was treated as a serious endeavour with real world consequences. My doctoral work was not theoretical, it was connected to live deployments, to industry partners, to the actual infrastructure of a digitally transforming Europe. That grounding is something I carry into everything. I am deeply sceptical of AI research that exists purely on paper. The question I ask of every system I work on is the same one I was trained to ask at TUS: does this work in the real world, under real conditions, with real constraints? That instinct came from those years and it has never left me.

What advice would you give to current students or recent graduates from your field?

Understand that the landscape you are entering is genuinely unprecedented. AI is not a tool that sits inside your profession, it is beginning to redefine the boundaries of what professions are. The students who will thrive are not necessarily those with the deepest technical skills, though those matter. They are the ones who can think across disciplines, who understand the human problems behind the technical solutions, and who are intellectually honest about what AI can and cannot do. I would also say: do not be seduced by the hype cycle. The most important AI work being done right now is unglamorous, rigorous, and deeply grounded in real problems. Find those problems and go and work on them.

What's one memory from your student days that stands out to you?

There was a moment during my PhD, a very late night in the lab, when a system I had been developing for months produced a result that indicated the core approach was sound. It was not a dramatic breakthrough. It was a quiet confirmation. But I remember sitting with that result and feeling a very clear sense that this work was pointing at something real, something that would eventually matter beyond the research context. That instinct turned out to be right. The ideas I was working on then connect directly to problems I am now helping solve at scale. Those moments of private clarity are the ones that actually shape a career.

How do you stay connected to the TUS community, if at all?

I stay connected because I think it is a responsibility, not simply a courtesy. The network that TUS represents, particularly for international students navigating a new country and a new professional environment, is genuinely valuable, and it only remains valuable if the people who have benefited from it put something back. I return for events and lectures when I can. I make time for conversations with current students and early career researchers. And I try to be honest with them about what the journey actually looks like, including the parts that are hard.

What does the idea of an alumni community mean to you?

It means something more durable than a professional network. Professional networks are built on current utility. An alumni community is built on shared formation, the experiences, the challenges, the intellectual environment that shaped how you think. That foundation does not expire. For international graduates in particular, it represents something even more significant, often the first place where you genuinely felt you belonged in a new country, where your ambitions were taken seriously. I carry that, and I want the way I engage with this community to honour it.

Finally, what's next for you?

The work that excites me most right now sits at the boundary of what AI can currently do and what it needs to become. We are at a genuinely interesting inflection point. The models are powerful, but the systems around them, the infrastructure for enterprise knowledge, the architectures for trustworthy AI in high stakes environments like healthcare, are still being built. That is where the startups I work with are operating, and that is where I want to contribute. I believe Ireland has a real opportunity to be at the forefront of this, not simply as a location for technology companies, but as a place where serious AI research and responsible AI deployment are happening together. That is the future I am working towards, and I intend to build it here.