Human Modelling and Knowledge Engineering

As industries and societies evolve, people are increasingly faced with the challenges of digital transition and the urgent need to upskill.  At the same time, the rapid rise of artificial intelligence is creating unprecedented opportunities — but also raising questions about how humans and intelligent technologies can work together effectively. Around the world, it is becoming clear that progress depends not only on technical advances in AI, but also on a deep understanding of human behaviour and knowledge processes. Human modelling and knowledge engineering therefore play a pivotal role in building systems that foster meaningful collaboration between people and machines, ensuring that technology adapts to human needs while supporting learning, decision-making, and long-term well-being.

Objectives

The Human Modelling and Knowledge Engineering considers effective collaboration between humans and intelligent technologies as the key to addressing these challenges. Through this approach, the group is building hybrid intelligence, where human strengths and AI complement and reinforce each other.

The interdisciplinary team brings together expertise in human modelling and knowledge engineering to develop personalized, human-centric technologies that support upskilling, adaptability and performance in the digital era.

Scope of expertise

To achieve this, the group drives innovation by:

• Modelling Human Behaviour
  The group models human behaviour to capture how people think, feel and act, enabling technology to better understand and adapt. Building on this deep understanding, it develops Human Digital Twins: smart, virtual counterparts that represent a person’s skills, learning journey and interactions in real time. These digital twins enable personalized feedback, tailored learning paths and seamless human-AI collaboration – empowering individuals to grow with technology by their side.
• Combining Knowledge Engineering with Generative AI
  The team envisions integrating Symbolic AI and Generative AI to create hybrid systems capable of transforming raw data into meaningful, interoperable knowledge. This research line focuses on leveraging symbolic reasoning to structure and formalize information, while using generative AI to enhance flexibility, creativity and user interaction. The goal is to support informed decision-making, improve the transparency of AI-driven outcomes and ensure that knowledge acquisition and use remain sustainable and interoperable over time. By combining the strengths of both approaches, this work aims to build trustworthy, human-aligned AI systems that evolve alongside complex real-world needs.
• Designing Smart AI that Adapts to Humans
  The group develops adaptive, AI-powered solutions that not only perform but also evolve with humans. By combining human modelling with real-time adaptation, these solutions employ Human Digital Twins at the appropriate level of detail to tailor experiences. Designed to be transparent and usable, they help people understand and trust the decisions it makes. Beyond performance, this line of research assesses real human impact to ensure that technologies boost upskilling, well-being and long-term success.
• Advancing New Forms of Human-AI Collaboration
  The team advances the future of human-AI collaboration through Cognitive AI designed to mirror human reasoning, alongside social robots for more intuitive and personalized collaboration. The result is hybrid intelligence that amplifies human creativity, boosts performance and enhances human upskilling and well-being, paving the way for a future where humans and AI thrive together.

Join us in shaping a future where technology empowers human potential!