August 2024

Tiffany Matej Hrkalovic PhD Student at Vrije University Amsterdam & Delft University of Technology The enigma of human willingness and ability to cooperate has been a topic of interest for millennia. However, due to the recent technological developments in designing intelligent systems and their potential usage in cooperative settings with humans, newer research is steered […]

Lea Krause PhD candidate at Vrije Universiteit Amsterdam The project addresses the critical need for cultural diversity in multilingual datasets used to train and evaluate language models and conversational agents. Current practices often involve translating English-centric content, which limits the cultural authenticity and applicability of these datasets across different regions. For example, evaluating models using

Zakaria Abdelmoiz Dahi Researcher-Lecturer Quantum computation is based on quantum mechanics principles, which allows it to gain a computational speedup over its classical counterpart, especially in combinatorial optimisation. The Quantum Approximate Optimisation Algorithm (QAOA) is a recent and promising quantum optimisation technique. It is expressed as a parameterisable quantum circuit whose parameters control its efficiency.

Alexander Hepburn Postdoc at University of Bristol Perceptual distances model a distance between two images, and are often designed to replicate certain processes in the human visual system, or optimised to mimic the decisions in a set of human perceptual judgements. Assuming Barlows hypothesis, that the brain seeks to minimise the amount of redundant information

Stefano Teso Senior Assistant Professor at CIMeC and DISI, University of Trento There is an increasing need of Artificial Intelligence (AI) and Machine Learning (ML) models that can reliably output predictions matching our expectations. Models learned from data should comply with specifications of desirable behavior supplied or elicited from humans and avoid overconfidence, i.e., being

Luuk de Jong Master student at Universiteit Leiden This project investigates the integration of a reject option in machine learning models to enhance reliability and explainability. By rejecting uncertain predictions, we can mitigate risks associated with low-confidence decisions, meaning the model will be more reliable. The core contribution of this work is the development and

Patrick Lang B.Sc. at N4 N4, a leading provider of procurement platforms in the automotive sector, is facing the challenge of making its catalogs for car parts (N4Parts) more user-friendly. These catalogs are used by customers both to purchase parts and to obtain information, such as installation instructions and maintenance intervals. The use of such

Jeff Clark Research Fellow at the University of Bristol With the widespread deployment of AI systems, it becomes increasingly important that users are equipped to scrutinise these models and their outputs. This is particular true for applications in high stakes domains such as healthcare. We propose to conduct research in the context of explainable AI,