Victor Mateevitsi
Victor Mateevitsi is an Assistant Computer Scientist at Argonne National Laboratories (ANL,) where he is a member of the Argonne Leadership Computing Facility (ALCF). He joined ANL in 2020 and he holds a PhD in Computer Science from the Electronic Visualization Laboratory at the University of Illinois at Chicago (UIC).
Victor is already establishing himself as a rising leader in the technology industry, from having been a TEDx speaker to being named in Crain’s Chicago Business Magazine’s “20 in their 20s” feature, and the Illinois Technology Foundation’s “Fifty for the Future.”
Among other accolades, he spent a summer at DreamWorks animation contributing to the development of Premo, the award-winning animation platform behind several Oscar-nominated movies. It’s been said that “Victor is unstoppable,” a tribute to this player on the Greek national ice hockey team at two World Championships.
Congratulations to ANL’s Victor Mateevitsi for his recognition as an HPC-AI Vanguard.
Who or what has influenced you the most to help you advance your career path?
My career in advanced computing has been shaped by the guidance and encouragement of several key individuals whose influence has been nothing short of transformative. If I had to pinpoint one person who had the greatest impact, it would be Maxine Brown, the retired director of the Electronic Visualization Laboratory at the University of Illinois Chicago. Maxine not only introduced me to the cutting-edge work at Argonne National Laboratory but also gave me the confidence to take bold steps in my career. Her belief in my potential and her encouragement to apply for a role at Argonne was a pivotal moment — one that opened doors I hadn’t even realized existed.
At Argonne, I’ve been incredibly fortunate to work within the Visualization and Data Analytics team. The mentorship I’ve received here has been invaluable, especially from my team lead, Joseph Insley, and our Division Director, Michael Papka. Their unwavering support, combined with their willingness to challenge me to think outside the box, has been instrumental in my growth. They’ve pushed me to explore new frontiers and to approach problems in innovative ways. It’s their leadership that continues to fuel my curiosity and determination to make meaningful contributions to the field. Their influence, both professionally and personally, has been a cornerstone of my journey, and I’m deeply grateful for their mentorship.
Equally transformative has been the mentorship of my PhD advisor, Andrew Johnson. He introduced me to the essence of scientific inquiry and taught me to think critically, remain curious, and maintain humility. His guidance laid the foundation for my research career and continues to shape the way I approach complex problems, especially when tackling new and uncharted areas.
I’m also deeply grateful for the many colleagues, mentors, and friends who have shaped my journey in ways both big and small. Each of these individuals has played a unique part in inspiring and supporting me, encouraging me to contribute back to our vibrant advanced computing community.
What is your passion related to your career path?
My passion lies in harnessing the power of advanced computing to transform complex data into actionable insights that not only drive scientific breakthroughs but also open entirely new avenues of exploration. There’s a creative thrill in developing visualizations that don’t just solve intricate problems—they lay the foundation for groundbreaking advances in science and engineering. Every challenge is an opportunity to push the boundaries of what’s possible.
One of the frontiers that excites me most is the integration of extended reality (XR) technologies into data exploration. Just imagine this: virtually stepping into the eye of a hurricane or feeling the force of a tornado through immersive haptic feedback. These aren’t just simulations—they’re experiences that can fundamentally shift how scientists engage with and understand data, offering an entirely new way to interact with the world around us.
And then there’s the promise of large language models (LLMs), like ChatGPT, which are already revolutionizing scientific inquiry. Picture being fully immersed in a virtual reality environment, where an AI assistant isn’t just a tool, but a dynamic collaborator. As you explore your datasets in real time, this assistant can help you analyze, visualize, and even hypothesize, guiding you toward deeper insights and accelerating the pace of discovery. It’s an exciting, uncharted space, and I’m thrilled to be part of it.
Is there a specific advance related to HPC-AI that you’ve thought about or been exposed to — possibly early R&D work — that shows particular promise by the end of the decade?
I believe we’re on the verge of a transformative advance in HPC-AI that could radically redefine how we generate new knowledge: the seamless, immersive collaboration between humans and AI. In this future, AI won’t just be a tool—it will evolve into an integrated co-pilot, working side-by-side with researchers in real-time.
Picture this: stepping into a virtual environment where you can walk among your data. Extended reality (XR) has already begun to dismantle the boundaries of data visualization, allowing us to view complex datasets in three dimensions. But there’s one crucial element missing: a natural, intuitive way to interact with that data. This is where AI steps in. By integrating advanced AI into these immersive spaces, we can overcome that gap. Imagine an AI assistant that not only analyzes data on the fly but also offers insights, identifies patterns, and predicts trends—all while adapting to your unique style of analysis.
This type of collaboration between human intuition and machine precision holds enormous promise. The AI assistant processes massive datasets at HPC scales, yet it doesn’t just crunch numbers — it engages in dynamic, conversational interactions. It answers questions, suggests hypotheses, and guides you through complex data landscapes as though it were an interactive, collaborative partner.
In this future, the researcher brings creativity, context, and critical judgment, while the AI contributes its unparalleled ability to process and analyze information at lightning speed. Together, they create a partnership that not only accelerates discovery but also enhances the depth and quality of insight we can achieve. The implications for scientific progress by the end of the decade are truly exciting.
Victor Mateevitsi on the Greek national hockey team (credit: Jason Pachos)
What are your thoughts on how we, the nation, build a stronger and deeper pipeline of talented and passionate HPC and AI professionals?
Building a stronger pipeline of talented HPC and AI professionals begins with igniting curiosity at an early age. As an Adjunct Research Professor at UIC, I’ve seen firsthand how students are already fascinated by AI. Many are actively experimenting with large language models or designing AI-centric projects for their theses. AI is accessible, ubiquitous, and inherently compelling—naturally drawing young talent into its orbit.
But when it comes to HPC, the story is different. Often shrouded in mystery, HPC is still perceived as something distant reserved for massive, expensive machines that only a few institutions can afford. Many students don’t even realize that HPC exists as a dynamic and exciting career path. That’s where we need to change the narrative.
To cultivate this talent, we must weave HPC into the fabric of STEM education. Introducing these concepts early—through school programs, internships, and hands-on experiences—can shift perceptions and highlight HPC’s critical role in powering AI and scientific innovation. Programs like Hour of Code, and Argonne’s Big Data Camp, alongside collaborative initiatives with organizations like the George Crabtree Institute for Discovery and Sustainability at UIC, are paving the way by making HPC more accessible to students. These efforts bridge the gap between academia and real-world research, offering students the chance to explore HPC firsthand, often sparking a passion that lasts a lifetime.
The future of HPC and AI hinges on our ability to inspire and nurture young talent now. If we can make these fields more visible, engaging, and accessible, we’ll not only strengthen the pipeline—we’ll accelerate the breakthroughs that will shape tomorrow’s world.
As HPC and AI converge, do you think AI is becoming the “dominant partner” at the expense of HPC? That is, will traditional, 64-bit supercomputing for many HPC workloads become de-prioritized; that lower-precision computing could “crowd out” traditional HPC?
I see the relationship between AI and HPC as a symbiotic one, rather than a competitive one. AI has an immense potential to accelerate scientific discoveries and enhance simulations by optimizing tasks and analyzing vast, complex datasets. But here’s the key: AI still fundamentally depends on the high-fidelity, precise data generated by traditional HPC simulations. In other words, while AI can speed up certain processes and make them more efficient, it’s built on the foundation of the robust, accurate simulations that HPC provides.
The growing trend toward lower-precision computing for AI workloads is often viewed as a challenge, but I don’t see it as a threat to 64-bit supercomputing. Instead, it’s more of a complement. HPC continues to be essential for scenarios where precision is paramount — areas like earth systems modeling, material science, or computational fluid dynamics. Rather than being pushed aside, traditional HPC is evolving to incorporate both established and emerging computing paradigms, ensuring that the two technologies can work together to deliver the best of both worlds.
Ultimately, the integration of AI and HPC is a powerful force for innovation. The strengths of each field complement and reinforce one another, enabling breakthroughs that neither could achieve alone. Together, they’re forging a path forward, advancing the frontiers of science and technology in ways that are truly transformative.
What does it take to be an effective leader in HPC and AI?
An effective leader in HPC and AI is someone who constantly stays at the forefront of innovation. This means being deeply aware of the latest technological advancements and knowing which research teams are breaking new ground. In HPC and AI, breakthroughs rarely happen in isolation, so a great leader knows how to foster collaboration and build diverse, multidisciplinary teams capable of tackling the complex problems we face today.
But leadership is about more than just technical expertise. To truly inspire and drive progress, a leader must lead by example. They combine a deep, relentless curiosity with a strong sense of humility—creating an environment where team members feel empowered to innovate without the fear of micromanagement. This means providing the time, space, and support for people to explore their ideas, which fosters creativity and trust within the team. It’s about allowing space for people to grow, make mistakes, and learn without fear of failure.
Mentorship is another pillar of effective leadership. By guiding students and early-career scientists, leaders help shape the next generation of HPC and AI experts. After all, every accomplished professional started out just like these emerging talents. A true leader recognizes this and takes the time to invest in others, helping them navigate their journey toward excellence.
At its core, effective leadership in HPC and AI is about more than just managing projects—it’s about inspiring innovation, nurturing growth, and building strong, resilient teams that can break barriers and redefine what’s possible.
The future vision question: What changes or challenges do you see for the HPC-AI community in the next five-10 years?
Looking ahead, one of the most pressing challenges will be addressing the issue of “hallucination” in LLMs. As AI becomes a cornerstone of scientific discovery, ensuring the accuracy and verifiability of the information these models generate will be crucial. AI often presents its outputs with an air of authority, but distinguishing fact from fabrication will require the development of robust validation mechanisms and guardrails to protect against misinformation. This will be especially critical as LLMs continue to integrate into research workflows, where trust in the data is paramount.
Simultaneously, AI is set to revolutionize the very nature of software development. As researchers increasingly rely on AI to generate code quickly and at high quality, we can expect a significant boost in productivity. But this also introduces new challenges: how do we ensure the reliability and security of code generated by AI? New best practices will need to emerge to safeguard against vulnerabilities while still maximizing the speed and efficiency AI brings to the table.
On the hardware side, I foresee a major shift in HPC architectures. Future HPC systems will see an increase in heterogeneity, incorporating an even broader mix of traditional CPUs, GPUs, and AI-specific accelerators to address the increasingly diverse demands of modern computational tasks. This trend will necessitate a parallel evolution in software ecosystems, as well as a transformation in the way we train and educate the next generation of professionals. To fully leverage these new architectures, we’ll need training programs that equip students and professionals with the expertise to navigate this new landscape and optimize these systems for their specific needs.
Would you like to share anything about your personal life?
I’m originally from Athens, Greece, where my love for ice skating began on the few small rinks that dotted the city—a far cry from the grand arenas you’d expect for ice hockey. With just two rinks, each only half the size of an NHL surface, I found myself drawn to the sport like a magnet. Even though I dabbled in karate, swimming, and basketball, it was ice hockey that truly grabbed my attention and wouldn’t let go.
The journey of ice hockey in Greece is something of an underdog story, reminiscent of the Jamaican bobsled team—one that most people don’t know about. When both rinks in Athens were eventually shut down, we didn’t give up. Our team kept pushing forward, organizing our own training camps in the Czech Republic, all at our own expense, because we refused to let the sport die.
That grit and determination paid off when I earned a spot on the Greek National Team. I was fortunate enough to represent my country at the World Championships in New Zealand and Bosnia and Herzegovina—experiences that shaped my life in ways few other sports could.
Today, I’m still keeping my skates sharp, playing recreationally in a local league at Johnny’s Ice House here in Chicago. Ice hockey has been far more than just a sport for me—it’s been a source of adventure, a teacher of perseverance, and a place where the power of teamwork and the pursuit of excellence became second nature. And I carry those lessons into everything I do.
