AI news ·
From Kalmár to LLMs, University of Szeged cements AI leadership with new MSc and 1.75 petaflops supercomputer
University of Szeged boosts AI: English-language MSc begins Sept 2026, backed by a 1.75-petaflop supercomputer. Work spotlights generative models and early disease risk.
University of Szeged Strengthens Its Key Position in AI Research
The University of Szeged (SZTE) is doubling down on AI. Starting in September 2026, the university will offer an English-language MSc in Artificial Intelligence built for serious research and high-impact applications.
This move builds on a long tradition. AI research in Szeged dates back to the 1950s, when Professor László Kalmár's lab developed one of Hungary's earliest experimental "robots," Katica. That foundation now supports a full stack of research, education, and innovation run through the Institute of Informatics and the Artificial Intelligence Competence Center, led by Professor Márk Jelasity.
Infrastructure that lets research move faster
SZTE introduced an AI-optimized supercomputer in the summer of 2025 with 1.75 petaflops of compute, built on Hewlett Packard Enterprise technology. It's available university-wide and built to support training, evaluation, and large-scale experimentation across projects.
Research focus: generative models and health
One flagship initiative, RAItHMA, studies how generative models (including large language models) behave in real settings-covering reliability, safety, and practical deployment. For researchers tracking LLM methods and applications, see Generative AI and LLM.
The university is also putting its extensive health data resources to work. Teams are building AI-driven predictive models to estimate disease risk-such as cancer-up to a decade in advance. This includes rigorous attention to validation, clinical relevance, and the legal and ethical dimensions of AI in healthcare.
Graduate programs that feed research and industry
The new MSc in Artificial Intelligence (from Sept 2026) will cover the foundations and practice of AI: machine learning, generative AI, data processing, and AI law and ethics. It offers two specializations:
- AI Researcher - for students aiming at academic or industrial research, with a focus on theory, methods, and publishing.
- AI Engineer - for building and shipping AI systems in software and product contexts, with emphasis on engineering and integration.
In 2027, a new Master's in Electrical Engineering will launch with three tracks: embedded systems, space technology, and artificial intelligence. It's unique in Hungary's Southern Great Plain region and spans hardware, software, and AI-useful for cross-disciplinary R&D.
Why this matters for scientists and research teams
- Access to serious compute for training and evaluation without leaving campus.
- Focused work on generative model reliability, reproducibility, and deployment.
- Health AI projects grounded in real data and measurable outcomes.
- A clear talent pipeline via MSc tracks aligned with research labs and industry needs.
- Collaboration across informatics, engineering, and domain sciences-shortening the gap from idea to experiment.
If you're building research programs or upskilling teams, explore AI for Science & Research for methods, tools, and training resources.
Leadership's stance
Professor Márk Jelasity highlights the supercomputer's role in supporting a growing portfolio of AI work across the university. Vice-Rector for Scientific Affairs and Innovation, Professor Zoltán Kónya, emphasizes a clear strategy: treat AI as a connected ecosystem-where education, research, and societal impact reinforce each other.
Szeged's direction is straightforward: build the infrastructure, run ambitious research, and educate people who can push AI forward-in labs, clinics, and industry.