Official Opening of the Eastern European Machine Learning Summer School – EEML 2024

The opening ceremony was attended by the Prime Minister of the Republic of Serbia Miloš Vučević, President of the Assembly of Vojvodina Balint Juhas, President of the Provincial Government Maja Gojković, Minister of Science, Technological Development and Innovation Dr. Jelena Begović, Provincial Secretary Prof. Dr. Branko Markoski, Mayor of Novi Sad Milan Đurić, and Dean of the Faculty of Technical Sciences, University of Novi Sad, Prof. Dr. Boris Dumnić.

In his opening remarks, Prime Minister Vučević stated that Serbia is a center of excellence in the development of artificial intelligence, as demonstrated today by the Institute for Artificial Intelligence of Serbia and the Faculty of Technical Sciences, Novi Sad.

"In 2020, the Government of Serbia adopted a strategy for the development of artificial intelligence, recognizing the necessity of investing in this field. By doing so, it acknowledged the need to master it. Serbia has comparative advantages, particularly in strengthening the IT sector, and by investing in young experts, professional staff, and institutions, we are creating a foundation for further development. The adoption of this strategy has evidently yielded results. Currently, a public debate on a new strategy is underway in Serbia, so we can face future challenges even more boldly and courageously", Vučević reminded.

"It is truly a pleasure to stand before you today. The primary motivation for establishing the state institute for artificial intelligence was to create an environment where our young people can engage in scientific research in the field of artificial intelligence", said the Acting Director of the Institute, Prof. Dr. Dubravko Ćulibrk.

The goal of EEML is to popularize machine learning and artificial intelligence across Europe, especially in Eastern Europe, and to encourage research in this field. Participants will deepen their knowledge on topics such as the basics of machine learning, multimodal learning, natural language processing, advanced deep learning architectures, generative models, and AI for science.