1. BNVKI rewards the PhD dissertation that brings the most original contribution in the field of artificial intelligence including, but not limited to, the methodological topics and impact area topics listed below.
  2. The award is intended for an individual researcher who has obtained their PhD from a Belgian, Dutch or Luxembourgish university between after December 1st 2023 and until December 31st 2024. The data of the public defence is used to determine the eligibility for the PhD dissertation award.
  3. The candidate submits a nomination cover page that includes: the name, affiliation, and contact details of the candidate; the title of the PhD dissertation; the date of the public defence of the dissertation; the names of the jury/examiners involved in its defence; a 2-page abstract of their work; a 1-page CV that includes the 5 most important achievements; a signed support letter by the promoter(s); and a link to the full dissertation. The candidate merges these documents in one PDF file and submits the document via Google form. The submission deadline is 30th April 2025.
  4. The candidate agrees that, when ranked first, the candidate will be nominated for the EurAI dissertation award.
  5. The candidates will be ranked by an independent jury of experts. The jury members will be selected based on diversity criteria, including geography, gender, and expertise.
  6. The award amounts to 1000€, for personal use, for the candidate that was ranked first. This award includes a certificate signed by the BNVKI board. BNVKI has no responsibility for any usage of the award. The award cannot be divided amongst several researchers.
  7. A runner-up will be awarded, for the candidate that was ranked second, by the expert jury. The runner-up award includes a certificate signed by the BNVKI board. The award cannot be divided amongst several researchers.
  8. The candidates that are awarded will be notified on 26 May 2025. The awards will be officially granted at the BNAIC 2025 conference. The winner and runner-up will be invited to give a talk at the BNAIC 2025 conference.

List of methodological topics

Methodological topics include, but are not limited to:

Bayesian Learning, Case-based Learning, Causal Learning, Clustering, Computational Creativity, Computational Learning Theory, Computational Models of Human Learning, Data Mining & Knowledge Discovery, Data Visualisation, Deep Learning, Dimensionality Reduction, Ensemble Methods, Evaluation Frameworks, Evolutionary Computation, Graph Mining & Social Network Analysis, Inductive Logic Programming, Interactive AI / Human-in-the-loop Methods and Systems, Kernel Methods, Knowledge Representation and Reasoning, Learning and Ubiquitous Computing, Learning in Multi-Agent Systems, Learning from Big Data, Learning from User Interactions, Logics and normative systems, Media Mining and Text Analytics, Natural Language Processing / Natural Language Understanding, Online Learning, Pattern Mining, Ranking / Preference Learning / Information Retrieval, Reinforcement Learning, Representation Learning, Robot Learning, Social Networks, Speech Recognition, Structured Output Learning, Time series modeling & prediction, Transfer and Adversarial Learning

List of research areas

Research areas include, but are not limited to:

AI and Law, AI and Ethics, Bioinformatics, genomics and biomedical, AI and Economics (game theory), AI and Educational science, Fundamental research in AI, Human-centered AI, Medical imaging, AI and Neuroscience, AI and Physics (complex systems), Scientific Machine Learning, AI Applications in Industry, AI for Scientific Discovery, AI and Social sciences, Robotics, AI and Gaming, AI and Entertaining, AI and Agriculture, AI and Finance, AI and Transport, AI and Automotive, AI and Social Media, Data Security, Healthcare, E-Commerce, AI and Art, AI and Astronomy