Applied Human-Centered AI


Artificial intelligence, as a fast-growing scientific discipline, has already changed our daily lives in fundamental ways. This SIG unites advances in various AI technologies using a human-in-the-loop approach for practical societal challenges. We closely connect with the AI Labs at Utrecht University and together aim to explore the interdisciplinary research cooperation among internal researchers and external partners from social, human-behavioral and geographical aspects.

Challenges in society

The digital revolution leads to new concepts and challenges in different practical domains of society. For instance, the increasing importance of sustainability and crowdedness of urban areas lead to different initiatives that may dictate the future of transportation via smart transport solutions such as e-mobility, shared mobility (e-vehicles and bikes) and (Connected) Automated Vehicles. These new concepts require new algorithms and simulation for analysing journeys with different modes of transportation. This includes e-bike, train, and bus, but also walking and cycling. There also is a need for new intelligent software applications that offer personalised, persuasive advice. Including psychological factors in mode of transport choice can strongly improve the prediction or description of human behavior and traffic flow. Besides effectiveness, efficiency, and user-satisfaction, social values such as safety, fairness, health aspects and environmental concerns need to be included.

Challenges in AI

As multi-disciplinary AI approach is pivotal for solving societal challenges, this SIG particularly focuses on the following AI challenges:

  • Data driven approaches: developing AI techniques including machine learning that process and interpret heterogeneous data from different sources, for example to improve operations and influence behavior of travelers, where interpretability of results has to be addressed.
  • Intelligent learning algorithms: developing intelligent algorithms such as optimization and reinforcement learning methods to solve decision problems in the practical domains.
  • Human-centered interactive AI: developing AI techniques to understand and predict human choice behaviour and to persuade people to make better choices (efficient, environmentally friendly, etc.), including Intelligent interactive information presentations, AI-induced persuasive technology, personalised interaction to maximise user satisfaction.
  • Intelligent system simulation: develop AI techniques such as agent-based simulation to analyse the design and performance of complex systems, including decision models and roles of different actors.

Organisation & Activities

The SIG has a close collaboration with the AI labs at Utrecht University. Together with the AI labs, we hope to provide an open community for supporting the multidisciplinary AI research both among UU researchers as well as with potential external partners.


Advisor AI labs


  • Call for seed fund proposals (such as developing new research proposals or outreaching activities): twice a year.
  • SIG gathering event at UU: twice a year (one internal for UU researchers and one open for national participants).
  • Newsletter about human-centered AI, data science and digital government: Monthly.
  • Networking events organized by the AI labs (both internally for UU researchers and externally with industrial partners): at least once a year with additional irregular events.
  • Special call for collaboration: irregular based on demand.


If you would like to discuss an idea for a SIG activity, please contact any of the coordinators. We also invite Utrecht University researchers to give input of your interest societal challenges. Please keep in touch with our fund call and upcoming activities (including ones at the AI labs) by joining the mailing list of the SIG through this form.