Current Trends in Artificial Intelligence 2021-2022

Spring 2022
Hugues Bersini, Johan Loeckx, Luc Steels (em.)
Course description

Artificial Intelligence is moving at an incredible pace. In this course, the latest progress  in state-of-the-art AI is introduced.  Over the course of ten guest lectures, experts in their field come to talk about their latest research.  

Next to the theoretical part, in the AI challenges,  students from VUB will apply learnt techniques in a team, to create an AI powered application! AI challenges aims to hone students’ soft skills like teamwork, empathy, communication and critical thinking while building functional products  in agile teams. This year we will build a research tool for lawyers.


TimePlaceRoomDate Range
13:30 – 15:30ULB (Solbosch) IRIDIA classroom (seminar room on the 5th floor) Fridays, 2nd semester
  1. 18/2 Hugues Bersini (ULB) – ON SITE
  2. 25/2  Hugues Bersini (ULB) – ON SITE
  3. 4/3  Guillaume Levasseur & Cédric Gilon – ON SITE
    • ​topic: Deep & recurrent neural network: two use cases
    • materials: slides
  4. 11/3 Hugues Bersini (ULB) – ON SITE
    • ​topic: “Can AI give rise to authentic artists”
    • materials: slides
  5. 18/3 Jose Carlos – ONLINE (ULB TEAMS)
  6. 25/3 Harry Bunt (Tilburg University) – ONLINE (ULB TEAMS)
    • topic: “Semantic annotation & computational pragmatics”
    • materials: slides
  7. 22/4 Rudolf Kruse (Universität Magdeburg) – ONLINE (ULB TEAMS)
    • ​topic: “Bayesian Networks: Theory and Applications”
    • materials: slides / book
  8. 29/4 Marco Saerens
    • topic: Fairness in AI
    • materials: slides
  9. 6/5 Pavel Silveira (HelloFresh) – ONLINE (ULB TEAMS)
      • topic: Transformers and forecasting
      • materials:
  10. 13/5 Pooya Zakeri (KULeuven) – ONLINE (ULB TEAMS)
    • topic: “Genomic Data Fusion through Kernel Methods”
    • materials: slides


Introduction to AI

Machine learning


The student is able to participatie actively in a scientific debate.

The student is aware of current trends in Artificial Intelligence en has the competence to judge different approaches and technologies.

The student can enumerate strengths and weaknesses of different AI technologies and under what circumstances they can be applied.

The student will also learn about open research questions to stimulate their own explorations in the field.


Attendance in the lectures is obliged (Friday afternoon). Each absence needs to be e-mailed beforehand.

60% of the grades come from the Start up labs programming assignment.

The other 40% come from an oral exam about the lectures.