The continuation of the consultations of the NCC team of Montenegro with the company Čikom and its sister company ITAS, was carried out on Friday, March 21, at the premises of the company Čikom. The meeting was attended by the CEO of the company Čikom, Vladan Tabaš, and the CEO of the company ITAS, Ivan Bošković, as well as representatives of the NCC team of Montenegro, Prof. Dr. Božo Krstajić and Prof. Dr. Enis Kočan. On February 1, the company ITAS began the implementation of the project “AI system for pathological analysis of adenocarcinoma (PathAI)”, which is co-financed by the Innovation Fund of Montenegro, and whose main goal is to improve the accuracy and efficiency of pathological analysis by applying innovative AI solutions. The ITAS team expects to collect and scan the first samples by the end of April, and the obtained images would then need to be processed on HPC resources. The NCC team recommended that ITAS apply to the call for HPC resources during the month of April, and presented the resources that can be obtained, the procedure for applying to the call and completing the application. It was agreed that the NCC team would be available to the ITAS company during the application period.
The University of Donja Gorica, in cooperation with EU House and Young European Ambassadors, is organizing a workshop and panel discussion on the topic “Artificial Intelligence and Media Literacy”. The event will be moderated by Igor Culafić, assistant at the UDG, master student in the “Artificial Intelligence” program and Young European Ambassador.
Workshop: Artificial Intelligence and Media Literacy
The workshop will demonstrate practical examples of using AI and HPC tools for creative and productive purposes, the presence of disinformation on the internet, how AI affects disinformation and how to recognize it. The presentation will take place on March 27 at 9:45 am, in the amphitheather A4 the University of Donja Gorica.
We invite students and all interested parties to attend this event and take the opportunity to develop practical skills in a critical approach to AI/HPC tools and become active participants in creating an ethical framework for the use of new technologies!
At the 24th International Symposium INFOTEH-JAHORINA (March 19-21, 2025), the paper “Transforming Matrix Problem Solving with Intelligent Tutoring Systems” will be presented. It explores the use of OCR and NLP technologies for automated matrix processing through an intelligent tutoring chatbot.
This effort was supported by the NCC Montenegro and resulted in a system that utilizes EasyOCR and the Qwen2-Math-7B-Instruct model for matrix operations with 95% accuracy. Implemented on our HPC cluster, it enables fast and precise processing of user queries, enhancing learning through AI-powered tools. The paper will be presented by Ms. Enisa Trubljanin and Mr Elvis Taruh, students at the Master AI program at UDG.
Click on image for sessions schedule for accepted papers.
In 2024, the EuroCC2/EuroCC4SEE project reached a new milestone, with 34 National Competence Centers (NCCs) showcasing significant achievements. This year’s review highlighted the collective drive to advance HPC, HPDA, and AI, strengthening competencies, capacities, and collaboration across Europe.
NCC Montenegro at the annual review meetingNCCs form 34 countries participated
A key focus in NCC presentations was user engagement, particularly with industry/SMEs. Through real-world HPC and AI use cases, Proofs of Concepts, and Success Stories, NCCs have bridged the gap between cutting-edge technologies and practical applications, fostering innovation across industries, academia, and the public sector. End-users have benefited from expert training, technical support, and subsidized access to EuroHPC supercomputing resources.
Great opportunity to exchange experiences and lessons learned
Collaboration remains central to EuroCC2/EuroCC4SEE. NCCs have deepened ties with other NCCs, CoEs, and EDIHs through mentoring, twinning, training and workshops. Joint initiatives, supported by EuroCC2 PMT and CASTIEL 2, have facilitated knowledge exchange, best practices, and white papers, accelerating Europe’s HPC/HPDA/AI ecosystem development. Training programs have equipped researchers, engineers, and industry professionals with essential skills to leverage these technologies effectively. The success stories presented reaffirm the project’s impact—enhancing scientific research, optimizing industry workflows, and improving public sector efficiency through smart solutions.
All NCCs presented what worked what did not in the precvous period
NCC Montenegro showcased Montenegrin companies, including UHURA, PAID MNE, IHMS, successfully utilizing European supercomputers to enhance the accuracy and efficiency of their innovative applications, complex simulations and advanced AI models. Additionally, the NCC Montenegro’s representative shared valuable insights on conducting HPC/AI study and training programs aligned with Smart Specialization strategy and highlighted successful collaborations with over 10 NCCs and CoEs in capacity building, industry practices and HPC awareness raising.
EUROCC4SEE and NCC Montenegro report
The 2024 review underscored EuroCC2/EuroCC4SEE’s role as a cornerstone of European HPC+ progress, driving user engagement, technological innovation and international collaboration. Looking ahead, the project remains committed to scaling impact, strengthening partnerships, and ensuring HPC and AI technologies remain accessible and beneficial to all.
Good opportunity for networking with EUROCC2/EUROCC4SEE representatives
The N-Ways to GPU Programming Bootcamp offers a comprehensive introduction to GPU programming. Participants will learn about various methods for adapting scientific applications to GPUs using NVIDIA CUDA, OpenACC, OpenMP offloading, and standard programming languages.
Throughout the bootcamp, attendees will work alongside teaching assistants to explore multiple GPU programming models. They will also learn how to analyze GPU-enabled applications using NVIDIA Nsight Systems. The program includes hands-on activities that allow participants to apply their newly acquired skills to real-world problems.
2 Days Hands-On Workshop: Hybrid Learning Experience jointly organized by BioExcel and supported by Sofia University “St. Kliment Ohridski”, Faculty of Chemistry and Pharmacy & Faculty of Physics, DISCOVERER Supercomputer and National Competence Centres in Bulgaria, North Macedonia, Romania, Serbia and Montenegro, this hydrid workshop will offer participants the chance to engage both on-site and online. The workshop will focus on the use of BioExcel core codes such as GROMACS, HADDOCK and PMX with a strong emphasis on hands-on practical sessions and guidance from leading experts in the field.
When & Where: May 21–22, 2025 | Sofia University, Bulgaria & Online
Researchers from the University of Donja Gorica presented a deep learning model for automated tuberculosis detection from chest X-rays at IEEE IT2025 conference. Using a convolutional neural network (CNN), the model classifies images as normal or tuberculosis-positive with an impressive 97.55% accuracy. This breakthrough has the potential to speed up diagnoses, reduce radiologist workload, and improve early detection rates, particularly in low-resource healthcare settings. By leveraging AI for fast and reliable medical imaging analysis, this research highlights the growing role of computer vision in modern healthcare and its ability to enhance efficiency and accuracy in disease detection.
ABSTRACT – This article presents a deep learning model that enables fast and accurate diagnosis of tuberculosis based on chest X-rays. The developed model uses convolutional neural network that enable the automatic classification of chest x-rays into one of two classes: Normal or Tuberculosis with a high degree of accuracy. The model achieved an accuracy of 97.55% on the test data set, indicating its potential to open new perspectives for medical professionals in establishing a tuberculosis diagnosis. This model can significantly speed up the diagnostic process, reducing the workload of medical workers and increasing their productivity in the fight against tuberculosis, one of the most common lung diseases.
