People

Max van Duijn is assistant professor at Leiden University’s Institute of Advanced Computer Science (LIACS). His research combines insights and methods from the humanities and sciences to study social intelligence, in particular perspective-taking and Theory of Mind. He is a lecturer at and co-initiator of the interdisciplinary BSc in Data Science & Artificial Intelligence (DSAI) and MSc in Creative Intelligence & Technology, member of The Young Academy (DJA, and active as a public academic at societal events and in the media.

Ramira is a PhD candidate specialising in Agent Modelling, Linguistics, and Theory of Mind. Working under Max van Duijn, her research explores decision-making in human-machine collaboration. With a background in Artificial Intelligence, she investigates how discourse and mutual understanding can bridge the gap between humans and machines. Her current work focuses on the pragmatic differences between models of intelligence, learning, and knowledge retention — with a special interest in the effects of theory of mind and norm-based, ‘common ground’ reasoning in cooperative scenarios involving incomplete information.

Lennard is a member of the SIM-Lab, where he explores how humans and AI systems can work together in high-stakes environments. His project, Interactive Inspection, investigates how inspectors can effectively collaborate with AI tools. A central question in his research is what it takes for people to trust and adopt AI applications—especially when these systems are never flawless. While “the human in the loop” is often seen as a safeguard, Lennard critically examines the hidden risks and assumptions behind that idea. His work is part of the broader AI4Oversight initiative.

Sabijn is a PhD Candidate within the field of Natural Language Processing (NLP) and linguistics. She is supervised by Max van Duijn, Gijs Wijnholds, and Suzan Verberne. Her current research focuses on the benefits of narrative data as pre-training data for small language models (SLMs).

Aida is a PhD candidate working at the intersection generative AI, media, and cultural bias. With a background in the humanities, she brings her experience studying race and gender in film and television into the world of machine learning. Her current research looks at how racialized and gendered narratives, especially around Middle Eastern migrant women in Nordic media, are echoed or reshaped by AI systems. She’s particularly interested in what happens when these models are asked to generate stories or scripts: do they simply reproduce the same affective biases and emotional tones found in human-written media, or can they do something different? Through prompt design, embedding analysis, and fine-tuning experiments, Aida research how stereotypes get reinforced or maybe even challenged by generative AI.

It is a familiar phenomenon: you ask the assistant on your phone to call your mother, but it calls a friend instead. Tom Kouwenhoven investigates how humans and Artificial Intelligence (AI) can better communicate with each other, so that these kinds of situations will no longer occur in the future.

As collaborating PhD student on this project, Bram did data collection and analysis of stories with tools from Natural Language Processing (NLP). His background is in Philosophy of Science and Social Science. 

Werner collaborated on this project as researcher. Drawing on a background in art and cognitive science, he (re)designed various clinical mindreading tasks both visually and textually, and designed a public science event for the project.

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.

Having finished the research Master Linguistics (Utrecht University), Li worked as an associate researcher on the “A Telling Story” project. Within this project, she focused on children’s use of emotional language to investigate socio-cognitive competence and the link with Theory of Mind. 

After a multidisciplinary background in cognitive sciences at McGill University, Lola joined the CIL to collaborate on the “A Telling Story project”.

Isabelle was involved from the very start of the project when it was still a pilot study (early 2019). She helped with setting up the project protocol, data collection infrastructure, and did many story workshops in day cares and schools.

Yasemin was like Isabelle involved in the early stage of the project. She introduced the storytelling workshop into the community centre she was involved, assisted with the workshop in many schools and transcribed a lot of stories.

Nikita worked in 2021 in the project and assisted with collecting stories, but also transcribed a lot of stories. She also designed promotional materials for the project, such as a news letter and story book.

Iris helped us with collecting data by establishing conections with schools in the south of The Netherlands and transcribing stories.

In the finishing stages of A Telling Story, Lieke helped creating the SIM lab website and started developing lesson material for Lil’Scientist. Furthermore she helped with small organisational and educational tasks like planning and checking and grading exams and projects.