We are excited to invite students, researchers, and professionals to our 2-day hands-on short course on Web Programming with Python, Flask and HPC-enabled Machine Learning.
Registration open until 16 Apr 2025.
This dynamic course is designed to introduce participants to web development using Python and Flask, while exploring how machine learning applications can be accelerated with High Performance Computing (HPC). Whether you’re a beginner or looking to extend your skills to include scalable ML solutions, this course is the perfect opportunity to learn from experienced instructors and work on real-life examples. More information abou t the course can be found at [link].
Course Schedule Part 1: Thursday, April 17, 2025 Starts at 8:00 AM University of Donja Gorica (UDG)
Part 2: Saturday, April 26, 2025 Starts at 9:00 AM University of Donja Gorica (UDG)
What You’ll Learn
Fundamentals of web development with Python and Flask
How to design and deploy simple web applications
Integration of machine learning models into web apps
Basics of HPC and how to run ML workloads efficiently
Real-world applications and interactive coding sessions
On 8 April 2025, the NCC Montenegro team—Tomo Popović, Ivan Jovović, and Elvis Taruh—visited COINIS, a leading Montenegrin digital marketing and ad tech company, to discuss potential collaboration in high-performance computing (HPC) and AI. We were warmly welcomed by our hosts, Ms. Tamara Pavlović and Ms. Aida Ismailisufi.
Visit to Coins to discuss HPC opportunities
The NCC team introduced the EUROCC2/EUROCC4SEE project and discussed how COINIS could leverage HPC resources for advanced data analytics, AI-driven personalization, and generative AI applications. Opportunities through EuroHPC calls, including FFPLUS, were presented, alongside examples of successful industry use cases.
Further collaboration was discussed, including POC project support and joint capacity-building activities. A follow-up is planned to define a concrete use case and collaboration with regards to a possible application process.
There was around 10 people from the company interested in the presentation
We have just enrolled over 25 people interested for the Prompt Engineering course. The course is implemented as a self-paced online course via LMS. We mainly enrolled students at BSc and MSc level, but there are few people coming from the industry sector (mainly IT). Most of the students are from Montenegro, but we have a couple of people coming from Bosnia and Serbia. Our target is that all of the enrollees finalize their work by 1 May.
The course starts on 7 AprilThis is a self-paced online course implemendet via LMS platform
As part of the ongoing H2020-MSCA TRACEWINDU initiative to foster digital innovation and transparency across value chains, a hands-on workshop on chatbot development using Large Language Models (LLMs) and the Azure platform was held at the National Competence Center for High-Performance Computing (NCC Montenegro), hosted by the University of Donja Gorica (UDG).
This workshop was implemented as a cross-collaboration of TRACEWINDU and EUROCC2/EUROCC4SEE ptojects
The workshop brought together a vibrant group of PhD, Master’s, and Bachelor students, alongside AI and HPC researchers and mentors from UDG—key TRACEWINDU and EUROCC4SEE project partners—highlighting the growing interest and expertise in cutting-edge AI technologies across disciplines.
Leading the session were Ms. Daliborka Nedić and Ms. Senka Gajinov from DunavNET, an innovation-driven technology company and core partner in the TRACEWINDU consortium. Their expert lecture provided attendees with valuable insights into the rapidly evolving world of generative AI and practical guidance on building intelligent chatbot solutions using Microsoft’s Azure OpenAI services.
Around 20 people attended, mostly PhD, MSc and BSc researchers interested in AI and HPC
The workshop covered key concepts such as:
The fundamentals of Large Language Models (LLMs) and their applications in chatbot development
Integration of LLMs within the Azure AI ecosystem
Best practices in prompt engineering and knowledge grounding
Real-life use cases aligned with transparency, automation, and user engagement in value chains
Beyond chatbot development, the discussion extended to the integration of computer vision models—particularly those aimed at automating data collection in value chains—and the use of HPC resources to support their deployment. Participants explored ideas for combining conversational AI interfaces with real-time computer vision capabilities, opening up possibilities for smarter, more interactive systems across agri-food and other sectors.
This collaborative brainstorming set the stage for future joint initiatives, where chatbots could serve as intuitive front-ends to complex AI models running on high-performance computing infrastructures—bridging accessibility and computational power for impactful solutions. This workshop is part of a broader capacity-building effort within TRACEWINDU and EUROCC4SEE, designed to empower young researchers and professionals with the tools and knowledge needed to innovate responsibly in the age of AI TRACEWINDU continues to bridge digital technologies and real-world value chain transformation.
Ms Daliborka Nedic and Ms Senka Gajinov from DNET at UDG
The Fortissimo Plus (FFplus) project recently concluded its first Open Call for Business Experiments, aimed at encouraging small and medium-sized enterprises (SMEs) to adopt High-Performance Computing (HPC) technologies. Launched on June 21, 2024, and closed on September 4, 2024, the call attracted 126 proposals from 220 organizations across 30 European countries. After a rigorous evaluation process, 19 sub-projects were selected for funding, involving 43 organizations, including 34 SMEs, demonstrating the initiative’s success in promoting HPC adoption among SMEs.
Summary of FFPlus Open Call 1 results (image: FFPlus)
Among the selected sub-projects is “Transforming Business Culture and Hiring Through High-Performance Computing GenAI-HPC4WB,” a notable initiative from Montenegro by a startup company called Recrewty. This project aims to revolutionize recruitment processes in the Balkan region by integrating generative artificial intelligence (AI), machine learning, and HPC. By analyzing psychometric data, CVs, and interviews using AI models tailored to regional languages—Montenegrin, Serbian, Bosnian, and Croatian—the project seeks to enhance hiring accuracy and efficiency. Utilizing HPC resources enables the processing of large datasets, improving the scalability and precision of these AI-driven assessments.
It is great to see Montenegro on this map (image: FFPlus)
The success of the GenAI-HPC4WB project underscores the growing competence and innovation capacity within Montenegro’s tech community. The HPC Montenegro team played a pivotal role in supporting the proposal’s development, reflecting the country’s commitment to advancing HPC applications and fostering collaboration between academia and industry. This achievement not only highlights Montenegro’s active participation in European HPC initiatives but also sets a precedent for future projects aiming to leverage advanced computing technologies to address regional challenges.
A team of researchers from the Center for Computer Science of the Faculty of Science and Mathematics, through the EuroCC2/EuroCC4SEE project, with the support of the NCC team of Montenegro, has gained access to the resources of the Leonardo HPC supercomputer. These resources will be used for the efficient development of a system for automatic segmentation of 3D views of mechanical assemblies obtained using 3D scanners. Identification of assembled parts and their relative positions is an important step for reverse engineering, automation of the disassembly process, quality control, AR and VR, etc. These activities are carried out within the project “AI segmentation and inspection by 3D scanning”, in cooperation with partners from France.
Successful application for HPC resources at Leonardo (Benchmark call)
Access to HPC resources is provided for a period of three months, through a successful application to the Benchmark call. During this period, the goal is to demonstrate the ability to efficiently use advanced computing resources, thus earning the right to apply to the Regular call for HPC resources
Mr Aleksandar vesovic defended his BSc thesis on the use of AI and HPC to develop a solution for attendance records in schools or universities. His mentors were Stevan Cakic and Tomo Popovic. He defended his theses on Friday, 28 March.
The theses and presentation discussed the integration of AI models into a web application and HPC integration
ABSTRACT – This thesis addresses the challenge of tracking student attendance in lectures through facial recognition. The aim of the research is to develop and implement a system that allows for automatic and accurate attendance tracking, thereby eliminating traditional methods that are often prone to errors and manipulation. The study analyzes the latest technologies in artificial intelligence, machine learning, and high- performance computing ( HPC) to achieve optimal accuracy and system efficiency. The implementation was tested on a sample of students and demonstrated high accuracy in facial recognition and attendance recording. This work also considers ethical aspects and p r ivacy concerns, given the sensitivity of the data collected and processed. The results suggest that applying facial recognition technology in an educational setting can significantly improve administrative processes while maintaining student security and privacy. Finally, possible future applications and recommendations for further system discussed.
HPC4S3ME and EUROCC2/EUROCC4SEE team members mentored and supported this research
