Across two focused sessions, the course covered key aspects of modern web development and machine learning integration. The first session introduced the development of dynamic web applications using Python and Flask, emphasizing structured user management, authentication systems, clean interface design, and automated email notifications to enhance functionality.
Mr. Ivan Jovovic was responsible for second part that took place on 26.4.2025.
The second session built on this foundation by integrating machine learning models for real-time image recognition within the web application. Participants worked on deploying pre-trained AI models, handling image uploads, and managing prediction outputs, with a brief overview of how high-performance computing (HPC) resources can support model training and updates.
There was about 20 people in this hands on session
Together, these sessions demonstrated a complete workflow — from backend development to AI model integration — highlighting how advanced technologies can be combined to create intelligent, scalable web solutions.
The University of Donja Gorica and NCC Montenegro are organizing a panel discussion within the hashtag#EuroCC project, a European initiative dedicated to the development of national competence centers in the field of high-performance computing, artificial intelligence and big data analysis.
The event brings together successful UDG alumni and researchers, who today lead innovative companies and projects in Montenegro and beyond. Through personal stories and practical insights, speakers will show how knowledge from AI and HPC can become key levers for career development.
Panelists:
Anton Jurovicki – CEO & Co-Founder, Coinis | The founder of the zaposli.ME platform
As part of our ongoing efforts to foster industry collaboration, the National Competence Centre (NCC) Montenegro recently conducted a follow-up consultation with representatives from Alicorn, Mr. Milutin Pavićević and Mr. Andrija Vučković. The meeting focused on exploring how High-Performance Computing (HPC) can be integrated into Alicorn’s development workflows, particularly in areas requiring substantial computational resources. Discussions also covered opportunities for accessing EuroHPC resources through open calls, as well as potential collaboration on Proof-of-Concept initiatives and joint project applications. We will also explore future options for open calls by Fortissimo and Innovation fund od Montenegro.
This was a follow up visit to Alicorn, an innovative technology company from Podgorica
Alicorn shared several promising use cases where HPC could significantly enhance their operations, including advanced data analytics and AI model training. This aligns with NCC Montenegro’s mission to support SMEs in leveraging HPC and AI technologies for innovation and competitiveness. We look forward to continuing our collaboration with Alicorn and assisting them in navigating EuroHPC application processes, thereby contributing to the digital transformation of Montenegro’s tech industry.
We are excited to announce a one-day short course titled “From Personal Computing to HPC”, taking place on Tuesday, April 29, 2025, starting at 13:30 at the University of Donja Gorica. This is primarily for the students, but others are welcome, too.
Organized within the EuroCC2 project framework, this intensive training session is designed to introduce participants to the fundamentals of High Performance Computing (HPC) and how it differs from standard personal computing. Whether you’re a student, researcher, or tech enthusiast, this course will help you understand:
The evolution from personal computers to HPC systems
Core components of HPC architectures
The role of HPC in science, industry, and innovation
How to get started using HPC resources
This is the second time this year. We are now focused on students (MSc and BSc), but others are welcome, too.
Participation is free of charge, but registration is required. Don’t miss this opportunity to boost your computational skills and explore the world of HPC!
On April 17, 2025, the University of Donja Gorica successfully hosted the first part of the two-day course “Web Programming with Python Flask and HPC-enabled ML”, organized under the EuroCC Montenegro project. The event attracted over 70 enthusiastic students from various faculties, eager to deepen their knowledge in modern web development and the integration of High-Performance Computing (HPC) with machine learning. The first session focused on the fundamentals of web development using Python Flask, introducing participants to key concepts, tools, and techniques needed to build scalable and interactive web applications.
This was the first part (Day 1) od the short course.
The strong turnout and active participation highlighted the growing interest in the intersection of web technologies and advanced computing. This hands-on course not only provided practical skills but also encouraged students to explore how HPC resources can enhance machine learning workflows within web environments. The second part of the course, which will delve deeper into HPC integration and real-world ML applications, is scheduled to follow soon. The event marks another step forward in building digital competencies and fostering applied computing education in Montenegro.
There was around 75 attendees, mainly BSc and Msc students interested in Web programming and HPC/Ai integration
Mr. Ivan Jovovic was the lecturer today and the course was supported by mr Dejan Babic, mr Elvis Taruh and prof. Tomo Popovic, all in coordination with NCC Montenegro management and coordinators. We continue on 26. April 2025!
As part of its mission to strengthen high-performance computing (HPC) capacities in Montenegro, the National Competence Center (NCC) in HPC recently visited the local IT company Exploring, a growing SME known for its innovative data-driven solutions. The meeting served as an initial consultation aimed at introducing the EUROCC project, and presenting the range of support services provided by NCC Montenegro.
NCC team visited Exploring, an SME IT developer from Podgorica
During the visit, the NCC Montenegro team provided an overview of the EUROCC initiative and the ongoing efforts to enhance digital innovation through HPC, artificial intelligence (AI), and related technologies. The Exploring team was introduced to the NCC self-assessment survey, a tool designed to help companies evaluate their readiness for adopting HPC technologies. In addition, we identified a potential use case to migrate Exploring’s development processes of ML prediction models for BI, which involve handling large datasets and developing prediction models, to the computing infrastructure managed by NCC Montenegro. This move could significantly improve computing performance and scalability for their internal R&D workflows.
The meeting also explored the possibility of:
Launching a proof-of-concept (PoC) analysis to evaluate the benefits of HPC in a real-world scenario tailored to Exploring’s use case;
Joint participation in upcoming open calls and EU-supported innovation programs;
Establishing a long-term collaboration between Exploring and NCC Montenegro to unlock further innovation potential.
This consultation marks an important step toward bridging the gap between academic HPC expertise and the private sector’s innovation goals. NCC Montenegro looks forward to supporting Exploring in its digital transformation journey.
We concluded this consultations with an action plan for the coming months
The paper “Transforming Matrix Problem Solving with Intelligent Tutoring Systems” by E. Trubljanin, E. Taruh, S. Cakic, T. Popovic and L. Filipovic was presented at INFOTEH conference an is published by IEEE Xplore. Researchers from the UDG with support from HPC NCC Montenegro have developed an innovative intelligent tutoring system that leverages artificial intelligence (AI) and high-performance computing (HPC) to revolutionize how students learn matrix operations. This chatbot-based solution combines Optical Character Recognition (EasyOCR) with an advanced natural language processing model (Qwen2-Math-7B-Instruct) to interpret both text and image inputs, enabling it to perform matrix operations such as transposition, addition, and multiplication while providing clear, step-by-step explanations. Supported by the university’s HPC infrastructure, the system ensures high-speed processing and real-time feedback, achieving up to 99% accuracy in matrix recognition from high-quality images. Designed with education in mind, this AI-powered tutor enhances interactivity, understanding, and learning outcomes for students tackling complex linear algebra concepts, and sets the stage for future enhancements like handwritten input recognition and support for more advanced operations.
ABSTRACT – This paper presents the integration of optical character recognition (OCR) and advanced natural language processing (NLP) models for automated handling of matrices derived from images and textual inputs, all combined within an implemented chatbot. The motivation for choosing this topic arises from the practical experiences of the authors gained while working with groups of students who encounter the concept of matrices as part of their academic responsibilities. Through the analysis of their results and classroom interactions, it was observed that many students struggle with this area. This paper presents an innovative approach to enhancing matrix problem-solving by leveraging intelligent tutoring systems supported by High-Performance Computing, aiming to improve learning efficiency and student outcomes. By combining the EasyOCR framework and the Qwen2-Math-7B-Instruct model, operations such as transposition, addition, and multiplication of matrices are enabled. The system supports the input of one or two matrices, allowing the selection of operations through textual or image-based queries. The OCR component extracts numerical data from images, while the NLP model interprets user requests and executes operations accurately. The interface allows the addition of a second matrix image only when necessary, enhancing the system’s intuitiveness and efficiency. The results of the recognition accuracy of the OCR model of image input matrices of different dimensions show a high level of accuracy of 95%, while for 2×2 matrices they reach an accuracy of 99%. This work contributes to the development of AI-powered tools for mathematical operations and holds potential applications in education.
