We are pleased to announce that the research team from the Faculty of Science and Mathematics has published a scientific paper titled “Data augmentation for fuselage panel inspection via 3D point cloud segmentation” in the Journal of Electronic Imaging. The paper presents advanced data augmentation methods to improve fuselage panel inspection using 3D point cloud segmentation, contributing to more accurate and reliable AI-based inspection systems. The research was enabled by access to the Leonardo HPC supercomputing resources, granted through the EuroCC2 project, which allowed the team to process large datasets and develop high-performance models efficiently. More info at: https://doi.org/10.1117/1.JEI.35.3.031202
From 25 to 28 February, in Žabljak, within the framework of the traditional IT Conference – one of the most significant scientific and professional conferences in the field of engineering and information sciences, held with IEEE support (triple IEEE concept in engineering) – the EUROCC4SEE Conference will be organized, with both in-person and online participation of partners.
EuroCC 2 & EuroCC4SEE at IEEE IT2026 in Zabljak
The conference will gather members of the EUROCC4SEE team, representatives of National Competence Centres (NCCs), as well as representatives of companies, the business community, and the public sector from the region and beyond. According to current registrations, more than 200 participants are expected, confirming the strong regional and international character of the event.
As part of the conference, a training session and workshop will be organized in line with the strategic tourism development priorities of all EUROCC4SEE countries, entitled: “Application of HPC and AI to Enhance the Tourism Offer”, aiming to present the possibilities of applying High Performance Computing (HPC) and Artificial Intelligence in improving tourism services, data analytics, and the development of innovative digital solutions.
The conference program will also include presentations of research papers, proof-of-concept projects, and HPC success stories demonstrating the practical application of HPC infrastructure in science, industry, and the development of new technologies.
Special focus will be placed on two central panels:
Application of HPC in Science and Industry – Real Examples and Success Stories, bringing together representatives of academia, industry, and the public sector to exchange experiences and present concrete examples of HPC solution implementation;
Regional Cooperation and EuroCC Experience – EUROCC4SEE: What Have We Learned and Where Do We Go Next? Lessons Learned and Regional Experiences, focused on analyzing project results achieved so far, sharing regional experiences, and defining future directions for the development of the HPC ecosystem in Southeast Europe.
In order to strengthen cooperation with industry and institutions, B2B Meetings and Collaborative Initiatives Toward EUROCC3 will also be organized, enabling direct meetings with business partners, public sector representatives, and potential HPC resource users.
The EUROCC4SEE conference represents an important platform for knowledge exchange, enhancement of regional cooperation, and strengthening the application of HPC technologies in science, industry, and public policies, confirming the strategic importance of digital infrastructure and innovation ecosystem development in the region.
Podgorica, 13 February 2026 – The Faculty of Medicine at the University of Montenegro hosted a regional symposium dedicated to the application of High-Performance Computing (HPC) and Artificial Intelligence (AI) in healthcare and medical research.
The event was organized by NCC Montenegro, in collaboration with the Faculty for Information Systems and Technologies (UDG) and the Faculty of Medicine (UoM), within the framework of the EuroCC2 and EuroCC4SEE projects, with additional support from the AI-AGE research project.
Bringing together approximately 20 participants from healthcare institutions, academia, innovative companies, and regional partners from Bosnia and Herzegovina, the symposium aimed to strengthen collaboration and advance the adoption of AI and HPC technologies in the health sector.
From Vision to Implementation
The programme combined strategic presentations, regional cooperation sessions, and technical demonstrations, creating a comprehensive overview of the current state of HPC and AI in healthcare.
NCC Montenegro presented Montenegro’s role as a national reference point for HPC, High-Performance Data Analytics (HPDA), and AI development. The presentation traced the entire pipeline—from clinical and biomedical data collection to AI model development and HPC-accelerated deployment.
A central message of the event was clear: HPC in healthcare is not merely about computational speed. It enables rigorous validation, reproducibility, and scalable deployment of AI models in real clinical environments.
Use cases discussed during the symposium included radiology, digital pathology, cardiology, genomics, ICU monitoring, and public health forecasting
AI-AGE: Advancing Research on Ageing
A dedicated session focused on the AI-AGE project, which explores retinal fundus imaging as a potential biomarker for accelerated biological ageing.
The interdisciplinary team presented research results based on UK Biobank data and datasets collected in Montenegro. Findings indicate that the complexity of retinal microvascular networks may decline more rapidly in patients with chronic diseases, highlighting potential applications in early diagnosis and monitoring.
Speakers emphasized the importance of careful model validation, addressing training bias, and ensuring responsible clinical deployment. The discussion also highlighted the potential of EuroHPC resources to further strengthen research capacity and computational scalability
Technical Showcase: AI Solutions Already in Practice
One of the most dynamic parts of the symposium was the Technical Showcase, where companies from Montenegro and Bosnia and Herzegovina presented concrete AI and HPC-enabled healthcare solutions.
Among the showcased innovations were:
AI-powered colon cancer detection in digital pathology using deep learning on high-resolution histopathology slides
AI-driven IoT platforms supporting clinical decision-making and patient management
AI systems for Alzheimer’s disease care, including predictive digital twins and multimodal reasoning tools
HPC-supported computational simulations accelerating pharmaceutical drug development
A particularly valuable component of the session was the sharing of experiences from companies that successfully applied for and received EuroHPC computing resources. These examples demonstrated how access to supercomputing infrastructure directly enhances model development, testing, and product readiness.
Strengthening Regional Cooperation
The symposium also included a regional twinning workshop between NCC Montenegro and NCC Bosnia and Herzegovina.
The session focused on joint strategies for stakeholder engagement, cross-border resource sharing, and knowledge transfer. The discussion confirmed that the twinning model is an effective mechanism for strengthening the South-East European HPC ecosystem and facilitating access to European supercomputing infrastructure.
Such cooperation is particularly important as the region prepares for the next phase of European HPC initiatives and increasing alignment with the EU AI Act and broader digital strategies.
Addressing Systemic Challenges
The event concluded with an interactive panel discussion titled “Orchestrating the Ecosystem.” Participants addressed key challenges facing AI adoption in healthcare, including:
The healthcare data gap and fragmentation
Regulatory complexity, particularly in the context of the EU AI Act
The need for stronger partnerships between industry, academia, and healthcare institutions
While AI model architectures continue to mature rapidly, participants agreed that the primary bottlenecks lie in data heterogeneity, evaluation standards, and deployment constraints rather than algorithmic limitations.
Healthcare representatives acknowledged the growing importance of HPC and AI in medical research but emphasized the need to improve institutional readiness for strategic and sustainable adoption.
A Strategic Step Forward
The symposium concluded with a shared commitment to:
Position AI and HPC as strategic priorities in healthcare innovation
Continue expanding infrastructure and access to HPC resources
Invest in skills development and capacity building
Strengthen regional collaboration across South-East Europe
The event marked an important step in connecting research excellence, industrial innovation, and clinical practice—demonstrating that HPC-enabled AI in healthcare is no longer a future concept, but an emerging regional reality.
We are proud to highlight PAID MNE as a featured success story in the EuroCC2 & EuroCC4SEE Booklet — demonstrating how HPC is transforming financial analytics and algorithmic trading.
EuroCC2 & EuroCC4SEE Booklet
At the heart of PAID MNE innovations lies PAID-T (Price Action Intelligent Detection Trading) — a smart trading platform that leverages advanced algorithms and AI/ML to dynamically adapt to market movements, optimise investment strategies, and manage risk with higher precision. Traditional computing systems quickly reached their limits. To unlock the required performance, the team scaled their solution to the LUMI supercomputer, one of Europe’s most powerful HPC infrastructures. By enabling multinode execution and real-time task distribution, PAID MNE achieved over 1.2 million simulations in under 5 hours — a process that previously would have taken days. This acceleration enables processing billions of historical transactions in hours instead of days, rapid identification of critical market patterns and data-driven optimisation/ increased accuracy of trading strategies.
PAID MNE success story
This achievement, showcased through the EuroCC2/EuroCC4SEE project, demonstrates how supercomputing is becoming a powerful enabler of business innovation. PAID MNE’s journey is a clear example of how HPC and AI together can transform complex, critical data into faster, more profitable decisions.
DeepMark is a deep-tech startup developing learning-based watermarking and provenance technology for AI-generated content. It previously used EuroHPC JU resources after receiving one year of access to the Leonardo Booster partition through a Development call. DeepMark leveraged these resources to advance next-generation watermarking research and benchmarking.
Deepmark
As the research deepened, the need for additional compute grew. Following consultations with the NCC Montenegro team at the University of Montenegro, DeepMark applied for GPU resources via the AI Factory Playground Access.
DeepMark has been awarded 5,000 GPU hours on the Leonardo Booster partition, granted for three months. This allocation will support work on robust, learning-based watermarking for AI-generated content—improving resilience to real-world edits and AI transformations and strengthening provenance and authenticity at scale. With this new allocation, DeepMark will expand its experiments and validation under real-world constraints.
The Uhura Solutions project “Generative AI Intelligent Process Automation Platform” has received a positive evaluation and has been granted an extension, including 4,500 node hours on the Leonardo BOOSTER HPC system for a 12-month period.
The additional HPC resources will support Uhura Solutions’ ongoing research and development in advanced Generative AI and Large Language Models (LLMs) tailored for the financial sector. Leveraging Leonardo’s state-of-the-art computing capabilities, the project will scale experiments from smaller open-source models to larger LLMs, enabling deeper research into optimization techniques such as parameter-efficient fine-tuning (PEFT), quantization, pruning, and model alignment.
Leonardo HPC
The Generative AI Intelligent Process Automation Platform integrates fine-tuned LLMs, low-code development, and process automation workflows to significantly improve operational efficiency, reduce costs, and enhance customer experience in financial services. A key differentiator of the platform is its focus on industry-specific language and context, supported by carefully curated private datasets with strong attention to data quality, privacy, and compliance.
This extension and access to Leonardo BOOSTER represent a major milestone for the project. The additional computational power allows company to push the boundaries of financial-domain AI and accelerate the delivery of scalable, production-ready solutions for the European market
The Train the Trainer course was organized from 30 January to 5 February as a series of full-day, intensive lectures, delivered alongside the standard AI and multi-GPU computing courses. This workshop complemented the strong technical focus of the regular course with a dedicated educational track. While the regular course concentrated on hands-on skills for building, scaling, and optimizing AI workloads across multiple GPUs, the Train-the-Trainer track was specifically designed to equip future instructors with the knowledge and pedagogical tools needed to teach these topics effectively. With only a few HPC and AI centres across Europe offering such specialized education, this programme helps expand the network of trainers and institutions capable of delivering high-quality AI and multi-GPU courses at both national and European levels. Researchers from the National Competence Center (NCC) Montenegro participated in this course, further strengthening national capacities in advanced AI and multi-GPU training.
AI Train the Trainer Workshop
During the training event, participants developed a deep understanding of modern multi-GPU and distributed AI technologies, while also learning effective strategies for teaching these complex concepts. Guided by expert instructors, attendees explored state-of-the-art tools, frameworks, and best practices for scaling AI workloads, combined with pedagogical approaches, teaching materials, and hands-on experience tailored to support the delivery of their own courses. The lectures covered a broad spectrum of topics, including GPU architectures and access to HPC infrastructure; fundamentals of deep learning and the transition from CPU- to GPU-based workloads; distributed training with PyTorch (Distributed Data Parallel, model parallelism, PyTorch Lightning); large language models, fine-tuning techniques, and frameworks such as Hugging Face Accelerate and DeepSpeed; as well as computer vision, MLOps, Ray, Retrieval Augmented Generation (RAG), and hyperparameter tuning.
The training event was organised by NCC Poland, NCC Netherlands, NCC Hungary, NCC Belgium, NCC Italy, NCC Finland, NCC Sweden, all National Competence Centres for High-Performance Computing, CASTIEL2 and EuroCC2/EuroCC4SEE.
