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SUMMARY:AI for Science Course
DTSTART:20260520T070000Z
DTEND:20260520T150000Z
DTSTAMP:20260518T155000Z
UID:indico-event-3802@indico.ijs.si
CONTACT:events@slaif.si
DESCRIPTION:The full-day course will introduce AI methods suitable for use
  in science. It will also present examples of their use in different branc
 hes of science\, including life sciences\, envirnmental sciences and mater
 ials science. Finally\, it will present the Slovenian AI Factory and the o
 pportunities it offers to scientists via its AI-for-Science vertical.\nThi
 s course on the topic "AI for Science" is organized by the Slovenian AI Fa
 ctory (SLAIF). The course will be given by Professor Sašo Džeroski. The
  lectures will be in English.\nIn-person or on-line attendance is possible
 . Registration is mandatory. \nMore information on the course\nArtificial
  intelligence is already transforming science across many disciplines\, an
 d its future impact is expected to be even greater. Realizing this potenti
 al\, however\, requires addressing challenges specific to scientific work:
  ensuring that models and their predictions are explainable\, learning eff
 ectively from the limited labelled data that is typical in science\, integ
 rating data with existing domain knowledge\, and supporting open and repro
 ducible science through the formalization and sharing of scientific knowle
 dge. This course introduces AI methods developed with precisely these cha
 llenges in mind. \nThe course covers a range of methods suitable for use 
 in science\, including explainable machine learning — with trees and ens
 embles for multi-target prediction as key examples — that produce accura
 te yet interpretable (or explainable) models for complex scientific domain
 s. It also addresses learning from limited data through two complementary 
 paradigms: semi-supervised learning\, which makes use of unlabelled alongs
 ide labelled data\, and foundation models\, which bring representations le
 arned from vast data to bear on data-scarce problems. Further topics inclu
 de automated scientific modelling\, in which interpretable models of dynam
 ical systems are learned from time series data and domain knowledge\, and 
 semantic technologies and ontologies for representing and sharing scientif
 ic knowledge. \nThe course will also present many examples of applying th
 ese methods to problems from different branches of science. The methods wi
 ll be illustrated with concrete applications in life sciences\, environmen
 tal sciences\, and materials science. The course will conclude with a pre
 sentation of the Slovenian AI Factory and the opportunities it offers to t
 he scientific community. \nAttendees will leave with a good overview of t
 he current AI-for-science methodological landscape\, a grounding in applic
 ations to a variety of sciences and a clear picture of how AI factories (a
 nd in particular SLAIF) can support their work in the area of AI for Scien
 ce. \nInformation on the lecturer\nSašo Džeroski is Head of the Departm
 ent of knowledge technologies at the Jozef Stefan Institute and full profe
 ssor at the Jozef Stefan International Postgraduate School\, both in Ljubl
 jana\, Slovenia. He is also a visiting professor at the European Space Age
 ncy (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 SLAI
 S\, the Slovenian Artificial Intelligence Society.His research interests f
 ocus on explainable machine learning\, computational scientific discovery\
 , and semantic technologies\, all in the context of artificial intelligenc
 e 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 r
 elational learning\, and learning from data streams\, as well as automated
  modelling of dynamical systems.Professor Džeroski has lead (as coordinat
 or) many national and international (EU-funded ) projects and has particip
 ated in many more. He is currently the coordinator of a large national pro
 ject titled "Artificial Intelligence for Science". He is also the technica
 l lead of SLAIF\, the Slovenian Artificial Intelligence Factory. \nThe wo
 rk of professor Džeroski has been extensively published and is highly cit
 ed. It has attracted more than 28580 citations and has an h-index of 77 (i
 n the GoogleScholar database). Prof. Džeroski is the most frequently cite
 d computer scientist in Slovenia (according to the 2025 ranking by Researc
 h.com). \n\nhttps://indico.ijs.si/event/3802/
IMAGE;VALUE=URI:https://indico.ijs.si/event/3802/logo-1596601024.png
LOCATION:A/2-A214 - Velika predavalnica (Jamova)
URL:https://indico.ijs.si/event/3802/
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