NGO “IT Društvo”, in cooperation with HPC NCC Montenegro, organizes a special session – panel “HPC / AI applications – opportunities, challenges and perspectives” as part of the XXVI scientific-professional conference Information Technology, IEEE IT2022, to be held on June 4, 2022 in the village of Tepca in the canyon of the river Tara, municipality of Žabljak, Montenegro. This panel aims to comprehensively and multidisciplinary review the opportunities, challenges and perspectives of the application of Artificial Intelligence and High-performance Computing in our country and in the world. The panel will be organized in the beautiful ambiance of the Tara river canyon with competent participants, representatives of scientific and educational institutions from the country and the region, agencies and companies. The agenda is available at this link.
Mr Stevan Šandi awarded NVIDIA Academic Hardware Grant
Mr Stevan Šandi, a PhD candidate at UDG and NCC Montenegro team member, won NVIDIA Academic Hardware Grant for his PhD research under DASCAP project. He was awarded an advanced GPU hardware that will be used for AI and Data Science applications in agriculture domain. He will be experimenting with various computer vision prediction models. Doing experiments on a better GPU will significantly reduce the time to get all of the planned experiments done.
Invited Talk: AI in Energy Sector by Prof. Mladen Kezunović (Texas A&M)
University of Donja Gorica and HPC NCC Montenegro invited a special guest, prof. dr Mladen Kezunović, a Regents Professor at Texas A&M University and Member of the US National Academy of Engineering. Prof. Kezunović will give talk on Artificial Intelligence in Energy Sector. This lecture is part of the series of events pertaining to HPC/AI applications in the priority domains of Motenegrin S3 and in line with the EuroCC NCC Montengro goal for engaging industry with respect to HPC/AI applications . The event is planned for 9:30h on 30 May 2022. Due to a limited number of seats, please register using the form is available here. We are also providing a link for online access to the lecture on YouTube (click here for live video).
Summary – The topic of Artificial Intelligence/Machine Learning (AI/ML) and associated analytics rose to prominence as the huge amounts of data became available through the space exploration, weather projections and medical biogenetic investigations. The humans deployed AI/ML to create data models to automate the data analysis, which may be infeasible to do manually or by simulations of physical systems only. Social media and commercial outlets such as Google, YouTube, Facebook, Twitter, Amazon and others have used for a while AI/ML the analysis of huge data sets to develop data models to predict consumer behavior. The power system operators are lately experiencing huge amounts of data obtained through field measurements and external sources such as variety of weather and other ambient data.
This talk focuses on the role of AI/ML data analytics in managing and controlling future power system by predicting power system outages at different spatiotemporal scales. The importance of outage prediction is explored, and examples how the AI/ML analytics are recently used to successful predict the risk of transmission and distribution faults are explored. The use of the risk prediction maps to manage the risk of forced outages and mitigate their impacts, as well as how the risk analysis can be used to schedule participation of distributed energy resources to mitigate outages is illustrated with a few examples. The future trends are also outlined.
NCC Montenegro at the EuroCC F2F meeting in Frankfurt
EuroCC organized first F2F meeting at Frankfurt on 28.04.2022. Partners, who had worked together for more than a year online, met together and presented achievements of all participant countries in area of HPC, HPDA and AI.
NCC Montenegro participated in the meeting and discussions on the implementation activities. Sanja Nikolic and Luka Filipovic presented the accomplishments of Montenegrin team. In the second part of the meeting, the participants agreed on the next steps in the project and further cooperation.
AI Master program presented at Axon webinar
This semester, the AXON Association of Applied Psychology Students organized a series of multidisciplinary lectures linking psychology and artificial intelligence, entitled “The Era of Artificial Intelligence.”
During the last session held on April 28, Dr. Tomo Popovic presented a new Master Program in Artificial Intelligence, which is being implemented at the Faculty of Information Systems and Technologies, with the support of NCC Montenegro and the EuroCC project. The presentation was followed by over 30 participants.
EuroCC featured in the Round Table on Machine Learning Organized by Montenegrin Academy of Sciences and Arts
EuroCC and AIMHiGH/FF4EuroHPC projects were featured in presentations during the round table “Deep Machine Learning”. This event was organized by the Montenegrin Academy of Sciences and Arts. The event took place on March 21, 2022. at the Rectorate building at the University of Montenegro. The participant discussed artificial intelligence and deep learning use cases and practical perspectives. Researchers from AIMHiGH project gave presentation on development of IoT Edge Computer Vision Sensors for smart farms supported by HPC and AI.
Evaluation of trends in jobs and skill‑sets using data analytics: a Case study, by Dr Armin Alibasic et al.
Member of the EuroCC Montenegro National Competence Center team, Dr Armin Alibasic together with co-authors Himanshu Upadhyay, Mecit Can Emre Simsekler, Thomas Kurfess, Wei Lee Woon and Mohammed Atif Omar conducted research published in the paper titled “Evaluation of trends in jobs and skill ‑ sets using data analytics: a Case study” in the Journal of Big Data. The article is available at the following link.
APSTRACT – A novel data-driven approach is developed to identify trending jobs through a case study in the oil and gas industry. The proposed approach leverages a range of data analytics tools, including Latent Semantic Indexing (LSI), Latent Dirichlet Allocation (LDA), Factor Analysis and Non-Negative Matrix Factorization (NMF), to study changes in the market. Further, our approach is capable of identifying disparities between skills that are covered by the educational system, and the skills that are required in the job market. Novel data-driven approach is developed to identify trending jobs through a case study in the oil and gas industry. The proposed approach leverages a range of data analytics tools, including Latent Semantic Indexing (LSI), Latent Dirichlet Allocation (LDA), Factor Analysis and Non-Negative Matrix Factorization (NMF), to study changes in the market. Further, our approach is capable of identifying disparities between skills that are covered by the educational system, and the skills that are required in the job market.