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.
HPC/AI Workshop and student conference are organized in context of HPC4S3ME and AI Fusion projects
The event will include:
Presentation of key results and achievements of both projects,
NCC Montenegro and EuroCC2/EuroCC4SEE presentation,
Presentation of student projects,
Panel discussion,
Coctail and networking.
Location: AP Amphitheatre, University of Donja Gorica Time: 10:00am – 16:00pm
The full agenda:
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
NCC Montenegro is co-organizing industry-focused workshops and networking events to inspire innovative companies, SMEs and startups to learn how to improve their business processes and accelerate innovations with supercomputing HPC/AI opportunities. NCC experts provide HPC and AI technical expertise and infrastructure access, adjusted to the business environment and industry domains.
In cooperation with ICT Cortex (ICT Cluster for Information Technologies, Innovation, Education, Design and Technology Development in Montenegro)-gathering more than 40 founding members and 1800 IT experts, NCC Montenegro is organizing workshop “Supercomputing Opportunities for Industry Leaders” on 18th of Dec, to present HPC/AI systems and benefits, NCC services and activities, as well as EuroHPC infrastructure opportunities.
Montenegro’s ICT sector has been recognized as the catalyst for the development of an innovative economy and for strengthening the competitiveness and multiple industries. ICT industry is one of the fastest growing sectors in Montenegro accumulating more than €600 in 2022 (vs €124mn in 2012), achieving almost 10% of GDP (vs 4% in 2012) and 21% of country’s total exports (vs 3% in 2017), according to ICT Cortex /CEED Consulting analyses.
We believe that this workshop will increase awareness on HPC&AI opportunities, provide valuable insights and inspirational use cases to the members and partners of ICT Cortex, enabling them to discover supercomputing power to enhance their innovative business and industry competitiveness.
As part of the EuroCC2 cross-NCC knowledge-sharing online events, which provide a platform for exchanging experiences on best practices, collaboration models, and impactful results, NCC Montenegro participated in the workshop “Establishing Business Relations between SMEs and Academia” on November 7th.
NCC Montenegro highlighted its outreach and onboarding activities for SMEs, featuring collaborations between academia and industry through: HPC/AI workshops and training events; development/research/innovation activities, and collaborative projects/grant schemes. A notable success story from the FinTech sector detailed how ML/HPC supported solutions addressed business challenges, including implementation steps and achieved benefits.
NCC Bulgaria emphasizes collaboration with various industry sectors and academia to foster partnerships with SMEs in addressing industry specific challenges through scientific research, training events, algorithm development, HPC solutions, and efficiency and scalability studies. Examples of successful HPC collaborations include improving precision in furniture design and analyzing advertising channel efficiency.
NCC Norway shared insights into Norway’s power market and collaboration with SINTEF Energy. By transitioning power models to HPC, they reduced simulation times from two hours to two minutes, enabling enhanced scenario testing and platform scalability. This collaborative workshop demonstrated practical approaches across NCCs, emphasizing the shared goal of bridging the gap between academia and industry through HPC innovations.
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.
prof. Kezunovic from Texas A&M gave presentation on a nove approach to Risk managemement in energy sectorThe workshop took place on 25 october at UDGOver 60 people attendedHow AI/ML supported by HPC can help mitigate risk in energy sector?
Ms. Tamara Pavlovic defended her MSc thesis on the use of HPC/AI for creating prediction models for breast cancer detection on 23.10.2024. 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.
This research was done in th context of HPC4S3ME and with the support from EUROCC NCC MontenegroMs Pavlovic finalized her thesis during the Breast Cancer Awareness Month (‘Pink October’)
Mr Mato Martinovic defended his MSc thesis on 23 octiber 2024. His research focused on detecting plant deseases for applications in vineyards. He was experimenting with HPC/AI and computer vision. He is one of the latest graduates from the AI master program created under EUROCC project and his mentoring was done with the support of EUROCC NCC Montenegro.
ABSTRACT – This research analyzes the use of computer vision in the field of viticulture. The thesis describes problems in viticulture, computer vision and its use in this field. The paper analyzed the performance of ResNet50, VGG16 and MobileNet models in the classification of diseases and grapevine species. The models achieved accuracy of 98.67%, 97.28%, and 98.72% on the original test data set, while on the extended one, they achieved 87.47%, 72.07%, and 86.64%, respectively, when classifying diseases. In species classification, the models achieved accuracies of 70%, 78% and 88% on the original test data set, and 66%, 51% and 72% on the extended one, respectively. The VGG-16 model had the largest difference in accuracy over extended data, while ResNet had the smallest decrease in accuracy in both cases, which implies that ResNet generalizes the data better. The paper presents the process of creating a platform that allows users to post an image and receive a prediction value through a mobile application.
HPC/AI and computer vision for applications in smart viticulture
Mr. Luka Jeremic defended his MSc thesis on 23 October 2024. The title of the thesis was AI and applications in medicine. His research was mentored by HPC4S3ME team members and it was done in the context of AI master program at the Faculty for information systems and technologie at UDG. This program and Master students are supporter by EUROCC NCC Montenegro.
ABSTRACT – This research explores the application of artificial intelligence in medicine, with a focus on the classification of brain, liver, and blood cell diseases. The main objective is to evaluate the effectiveness of algorithms in recognizing and classifying diseases of these organs. Through the development of a prototype information system, the study analyzes how artificial intelligence can improve diagnostics and contribute to the advancement of personalized medicine. The methodology includes a literature review, the development of computer vision models, and the assessment of model accuracy using real medical data. The results show that models based on deep neural networks can enhance the accuracy and speed of diagnostics, allowing for more precise disease classification. The paper also highlights the barriers and challenges in implementing these technologies, including the need for ethical considerations and training of medical staff. The conclusions suggest that this approach has the potential to significantly improve medicine, but further research and refinement are necessary.
Mr Jeremic defended his master thesis on AI/ML and applications in medicine
