Building scientific and innovation potential to utilize HPC and AI for S3 Smart Specialisation in Montenegro
On 27 December, University of Donja Gorica hosted a discussion on active project results and progress. Ms Zoja Scekic, a young researcher on HPC4S3ME project gave a presentation on the project and its final results. Most notably she shared the experences from the HPC/AI Workshop and Students Conference that was the final event withing the HPC4S3ME project.
The University of Donja Gorica hosted the highly anticipated HPC/AI Workshop and Student Conference on Saturday, December 21st. This event served as a key platform to highlight the outcomes of the HPC4S3ME IPA project and the AIFusion training program supported by the Innovation Fund of Montenegro. Both projects were developed within the framework of EuroCC2/EuroCC4SEE, with support from the NCC Montenegro team. The events showcased significant advancements in high-performance computing (HPC) and artificial intelligence (AI) in Montenegro.
The workshop commenced with presentations on the results and achievements of the HPC4S3ME and AIFusion projects. Participants were also introduced to the activities and contributions of NCC Montenegro and the broader EuroCC2/EuroCC4SEE initiatives. These sessions underscored the critical role of collaboration and innovation in advancing HPC and AI capabilities.
A highlight of the event was the student conference, which featured 19 project presentations by student teams, primarily from MSc and BSc programs. These projects demonstrated the creativity, technical acumen, and forward-thinking approaches of the next generation of researchers and innovators. The diversity of ideas presented reflected the growing interest and expertise in leveraging HPC and AI for real-world applications. The project discussed HPC and AI applications in digital transformation of education, medicine, fashion, mathematcis, and tourism.
The day concluded with a dynamic panel discussion focusing on the potential of HPC and AI, emphasizing the importance of training, skills development, and success stories from academia and industry. Experts and participants engaged in vibrant discussions, exchanging insights and exploring the future possibilities of these transformative technologies.
With over 50 attendees, the event fostered a collaborative and engaging atmosphere, encouraging knowledge sharing and networking. The conference provided participants with an inspiring experience, leaving them motivated to explore further advancements in HPC and AI.
The event concluded on a high note with a cocktail reception, offering attendees the opportunity to network in an informal setting. This gathering reaffirmed the University of Donja Gorica’s commitment to fostering innovation and excellence in HPC and AI, further establishing its role as a regional leader in these critical domains. This was another successful cross-project collaboration.
The Book of abstracts can be accessed by clicking on the image below (link).
On Saturday, December 21st, the University of Donja Gorica will host an HPC/AI Workshop and Student Conference, where participants from the AIFusion and HPC4S3ME projects will present their results. This will be a great way of finalizing efforts in both projects!
The event will include:
Location: AP Amphitheatre, University of Donja Gorica
Time: 10:00am – 16:00pm
After the program, the socializing will continue with a cocktail.
Join us to celebrate the results and exchange ideas in the field of HPC and AI.
HPC4S3ME team presented a scientific paper called “Optimizing solar energy management using AI based systems” at the 8th International Symposium on Innovative Approaches in Smart Technologies that took place 6-7 December 2024 in Istanbul, Turkiye. The authors of the paper were Arnad Lekic, Anesa Abazovic, Dejan Babic, Ivan Jovovic, and Tomo Popovic. This research was a direct result of capacity building activity supported by the HPC4S3ME project.
Abstract— The research presented in this paper explores the possibilities of optimizing solar energy usage and managing solar panels in hybrid energy systems that use both solar energy and the electrical grid. A model has been created to track time series data and solar radiation in order to predict the expected solar energy yield. The goal of this research is to enable users to plan their energy consumption and maximize savings through optimal use of solar panels. This process involves collecting weather data, optimizing energy usage, and proposing a system implementation that can be used by both companies and end users.
The University of Donja Gorica (UDG) hosted a captivating lecture by Dr. Yang Jingxin, Associate Professor at the Robotics College (Artificial Intelligence College) of Beijing Union University (BUU). A distinguished expert in artificial intelligence, Dr. Yang has an impressive academic journey, including a Doctorate in Materials Science and Engineering from Tsinghua University and a National Visiting Scholarship at Rice University in the USA. Her extensive research bridges intelligent manufacturing and artificial intelligence, focusing on innovation and sustainability.
During her lecture, Dr. Yang provided an in-depth exploration of AI’s transformative potential, its cutting-edge applications, and the future trends shaping this dynamic field. She highlighted AI’s role at BUU and shared insights into the intersection of intelligent manufacturing and AI.
During November, two UDG researchers implemented a month long mobility at DunavNET as part of the TRACEWINDU MSCA H2020 project. Mr Ivan Jovovic and mr Dejan Babic, PhD students, engaged in productive discussions with DunavNET’s expert team members. The focus was on evaluating blockchain frameworks to identify the most suitable structure for ensuring transparent and secure wine traceability. They also analyzed data model requirements, highlighting the importance of data integrity and accessibility for tracking wine from production to consumption. During their stay, they went through a training on the utilisation of various AI tools and resource management on Azure platforms. An idea that will be pursued in their future research would be creation and use of chatbots for engagement of stakeholders. More on the TRACEWINDU project can be seen at the following link.
Two young researcher mobilities implemented through cross-pollination with TRACEWINDU project
The paper “Detection of Livestock Using Edge Devices” by E. Taruh, M. Raicevic, I. Jovovic, D. Babic, and T. Popovic, was presented at the 5th International Conference on Communications, Information, Electronic and Energy Systems, 2024 IEEE CIEES conference that takes place in Tarnovo, Bulgaria. The paper is result of research and experimenting in the agricultural domain throgh mentoring and cross-project collaboration.
ABSTRACT – This paper presents the development of a real-time system for detecting and monitoring large livestock using cameras connected to a Jetson Nano device and the YOLO v8 model for animal recognition (specifically cattle). The implementation of this system enables precise tracking of livestock movements and conditions, facilitating supervision and management on farms. The system provides real-time notifications and information crucial for efficient resource management. Model evaluation showed an accuracy of 65% after 35 epochs of training. The developed platform demonstrates potential for improving efficiency and safety in agricultural enterprises with possibilities for further enhancement and scaling.
We were privileged to host Dr. Silvija Seres, an esteemed thought leader in digital transformation, as part of our ongoing Digital Transformation course at the Faculty of Information Systems and Technologies. Her lecture provided profound insights into the current AI revolution, its critical role in shaping future industries, and its transformative impact on both personal and professional life. Dr. Seres shared valuable perspectives drawn from her global experiences, spanning across diverse fields and cultures. Her career path reflects an impressive journey through business innovation and technology, making her an inspiring figure for students and professionals alike. She spoke not only about the technical aspects of digital transformation but also about the need to maintain a life balance amid the fast-paced changes driven by AI and digitalization. She addressed challenges and opportunities specific to women in science and business, offering her own journey as a testament to the power of resilience and adaptability in traditionally male-dominated sectors.
The lecture was also a catalyst for dynamic discussions among students. They engaged with Dr. Seres on critical topics such as the importance of developing robust business models, defining a clear mission and vision, and securing investment to drive meaningful change. Her insights into the role of venture capital and other support mechanisms shed light on how businesses, especially tech-driven enterprises, can strategically position themselves in the market. This engaging session was a meaningful addition to the Digital Transformation curriculum, providing students not only with theoretical knowledge but also with real-world perspectives on what it takes to innovate and thrive in an era marked by rapid technological advancements.
About our lecturer: Successful developer of international technology companies, with focus on commercialization. Investor and board member, working with majors and startups in IT, finance, media and energy. Leader of large geographically distributed organizations in consulting, marketing and services. MSC Computer Science (Oslo), MBA (INSEAD), PhD Mathematical Sciences (Oxford University). International profile, with five languages and extensive living and working experience worldwide. Link: https://silvijaseres.com/
As planned, the invited lecture “Risk Management of Future Large-Scale Electrification” by prof. Mladen Kezunovic took place on 25 October 2024 in Enterpreneurial nest at UDG. Threre was over 60 attendees including students, academics from Montenegrin universities and representatives from the industry. This workshop was organized in the context of HPC4S3ME project and supported by EUROCC NCC Montenegro team.
What are the risks? Methodology for risk management and mitigation? What data do we have and how do we manage all that data? How can AI/ML supported by HPC help?
Dr. Mladen Kezunovic is a University Distinguished Professor at Texas A&M with over 35 years of expertise in power engineering. Renowned globally, Dr. Kezunovic has authored over 600 papers and consulted for 50+ companies worldwide. His extensive research and industry contributions, notably in fault modeling, data analytics, and smart grids, have earned him IEEE Life Fellow status and recognition from the US National Academy of Engineering.
Ms. Tamara Pavlovic defended her MSc thesis on the use of HPC/AI for creating prediction models for breast cancer detection on 23 October 2024. With the support from NCC Montenegro, Ms Pavlovic did her research in the context of the HPC4S3ME project and the focus was on AI and computer vision applications in medicine. From the motivational point of view, we congratulate Tamara for finalizing and defending her thesis during the Breast Cancer Awareness Month (‘Pink October’) as people around the world adopt the pink colour and display a pink ribbon to raise awareness about breast health.
ABSTRACT – Artificial Intelligence (AI) is revolutionizing numerous sectors, including medicine, by offering innovative methods for diagnosing, treating, and researching diseases. This master’s thesis focuses on the application of AI in the diagnosis of breast cancer, using computer vision algorithms to analyze mammographic images. Through a combination of convolutional neural networks (CNNs) and deep learning, models have been developed that identify malignant changes, potentially contributing to earlier and more precise disease detection. The thesis examines in detail how AI can improve the efficiency of screening processes, reduce the time required for diagnosis, and enable a more personalized approach to treatment. In addition to technological progress, ethical issues such as patient safety and the transparency of AI systems are also considered. The results of this study confirm that the application of AI in breast cancer diagnostics can significantly enhance medical procedures. The models tested, ResNet152 and DenseNet121, demonstrated quite good performance in classifying breast cancer. Their AUC scores, which exceed the threshold of 0.9, indicate their potential for use in clinical practice. These findings not only contribute to the improvement of diagnostic processes but also open up opportunities for further research and development of AI technologies in medicine.
