We research with games!
Here in the Game Research Lab (GRL) we use digital games as a medium for academic research. We consider entertainment games and 'serious' games equally valuable objects of study, and involve both in our work. The GRL develops novel computational and design approaches for creating, playing, and analyzing games; and pursue both the application of state-of-the-art AI research to games and new insights for AI from games. The GRL is fundamentally interdisciplinary and actively pursues collaborations that challenge the current understanding of games. Our research has strong links to HCI, cognitive science, social science, and digital humanities.
The Lab Team
Our group of player characters.
Mike is doing research on algorithms in game AI and how to apply them to practical problems, in the games domain and beyond (e.g. engineering, chemical, social media computing). He is involved in pushing AI use into new areas of game research, as with Team AI (human/agent as well as agent/agent cooperation). He is a regular co-organizer of conferences as IEEE CoG (formerly CIG) and an associate editor of the IEEE Transactions on Games.
Marcello A. Gómez-Maureira
Researcher and designer, drawn to projects that involve multidisciplinary challenges and the potential to build connections between them. Formally trained as mechanical engineer and video game developer, his ongoing research interests focus on the interplay between humans and interactive technology, as well as the prospects of designing the impact of technology on society and human emotions.
I moved to the Netherlands in 2014 to start my studies. Now researching the use of video games and gamification practices for education.
Alan Kai Hassen
Alan is interested in transferring Artificial Intelligence techniques developed for solving games (Go, Chess, Grand Turismo, etc.) to the Chemistry domain. His main research interest lies in Computer-Aided Synthesis Planning (compare: ESR7 @ ai-dd.eu). In his Ph.D. thesis, he combines several methods from different domains, including Reinforcement Learning, Deep Learning, Game Environments, Cheminformatics, and Multi-Objective Optimization.
Alan holds an MSc and BSc in Information Systems from the University of Münster. During his studies, he focused on Artificial Intelligence, Data Science, and Process Management.