The full-day course will introduce AI methods suitable for use in science. It will also present examples of their use in different branches of science, including life sciences, envirnmental sciences and materials science. Finally, it will present the Slovenian AI Factory and the opportunities it offers to scientists via its AI-for-Science vertical.
This course on the topic "AI for Science" is organized by the Slovenian AI Factory (SLAIF). The course will be given by Professor Sašo Džeroski. The lectures will be in English.
In-person or on-line attendance is possible. Registration is mandatory.
More information on the course
Artificial intelligence is already transforming science across many disciplines, and its future impact is expected to be even greater. Realizing this potential, however, requires addressing challenges specific to scientific work: ensuring that models and their predictions are explainable, learning effectively from the limited labelled data that is typical in science, integrating data with existing domain knowledge, and supporting open and reproducible science through the formalization and sharing of scientific knowledge. This course introduces AI methods developed with precisely these challenges in mind.
The course covers a range of methods suitable for use in science, including explainable machine learning — with trees and ensembles for multi-target prediction as key examples — that produce accurate yet interpretable (or explainable) models for complex scientific domains. It also addresses learning from limited data through two complementary paradigms: semi-supervised learning, which makes use of unlabelled alongside labelled data, and foundation models, which bring representations learned from vast data to bear on data-scarce problems. Further topics include automated scientific modelling, in which interpretable models of dynamical systems are learned from time series data and domain knowledge, and semantic technologies and ontologies for representing and sharing scientific knowledge.
The course will also present many examples of applying these methods to problems from different branches of science. The methods will be illustrated with concrete applications in life sciences, environmental sciences, and materials science. The course will conclude with a presentation of the Slovenian AI Factory and the opportunities it offers to the scientific community.
Attendees will leave with a good overview of the current AI-for-science methodological landscape, a grounding in applications to a variety of sciences and a clear picture of how AI factories (and in particular SLAIF) can support their work in the area of AI for Science.
Information on the lecturer
Sašo Džeroski is Head of the Department of knowledge technologies at the Jozef Stefan Institute and full professor at the Jozef Stefan International Postgraduate School, both in Ljubljana, Slovenia. He is also a visiting professor at the European Space Agency (Frascati, Italy). He is a fellow of EurAI, the European Association of AI, in recognition of his "Pioneering Work in the field of AI”. He is a member of the Macedonian Academy of Sciences and Arts and a member of Academia Europea. He is past president and current vice-president of SLAIS, the Slovenian Artificial Intelligence Society.
His research interests focus on explainable machine learning, computational scientific discovery, and semantic technologies, all in the context of artificial intelligence for science. His group has developed machine learning methods that learn explainable models from complex data in the presence of domain knowledge: These include methods for multi-target prediction, semi-supervised and relational learning, and learning from data streams, as well as automated modelling of dynamical systems.
Professor Džeroski has lead (as coordinator) many national and international (EU-funded ) projects and has participated in many more. He is currently the coordinator of a large national project titled "Artificial Intelligence for Science". He is also the technical lead of SLAIF, the Slovenian Artificial Intelligence Factory.
The work of professor Džeroski has been extensively published and is highly cited. It has attracted more than 28580 citations and has an h-index of 77 (in the GoogleScholar database). Prof. Džeroski is the most frequently cited computer scientist in Slovenia (according to the 2025 ranking by Research.com).