Enrico Liscio – TU Delft PhD student Participatory systems aim to elicit citizens’ stances on societal discussions to inform policy making. In particular, human values are a crucial component of citizens’ stances, since they are the drivers of our opinions and behaviors. AI can enable mass participation and process large quantity of citizens’ input. However,

Julian F. Schumann – TU Delft PhD student For humans to trust autonomous vehicles, they need to have confidence in the vehicles’ ability to reliably resolve space-sharing conflicts with other traffic participants in a safe manner – such as in the case of crossing or merging paths. Planning safe and efficient interactions for autonomous vehicles

Giovanni Franzese – TU Delft PhD candidate The adaptability of robot manipulators to many different tasks is currently constrained by systematic hard coding of each specific task. Recent machine learning methods like Learning from Demonstrations (LfD) and Reinforcement Learning (RL) have shown promising results in having fast reprogramming of the task using human demonstrations or

Jeroen G. Rook – University of Twente PhD candidate Comparing algorithms is a non-trivial task. Often, a set of representative problem instances are used to compare algorithms. However, these problem instances introduce biases in the comparison outcomes, which is often not taken into account. The confidence of the comparison can be strengthened by using statistical