AI-Augmented Engineering projects
To prepare future engineers from the various disciplines at TU Delft and skill them in AI-augmented science, design and engineering we want to stimulate the development of education on AI-Augmented science, design and engineering. We are happy to announce that the following three educational projects are currently in development across the TU Delft.
AI Enhanced Engineering Education at Civil Engineering and Geo Sciences (CEG)
Under the lead of Riccardo Taormina and Iuri Rocha, this project team aims to develop tailored teaching materials and guidelines. By first assessing best practices in AI-education, they will adapt these to the CEG engineering context and implement them in a pilot within the AI course (CEGM2003). They will then engage CEG colleagues in discussions on the pros and cons of using AI, sharing pilot outcomes, lessons learned, and guidelines.
AI in Design Education (IDE)
Dave Murray-Rust and Derek Lomas aim to build a community within and beyond IDE to explore and shape new approaches in Design Education. They will survey current and emerging uses of generative AI within design courses, hosting a series of sharing events to discuss, critique, and refine these practices. Their focus lies on mapping and articulating existing AI-enhanced practices rather than creating new tools, supporting a community-driven dialogue around evolving design education.
GenAI as a design tool in chemistry and chemical engineering (AS)
Led by Artur Schweidtmann, this project explores generative AI’s role in chemical engineering education. Through discussions with faculty leaders and workshops with AI education experts, the team will define an initial concept for incorporating generative AI into chemical engineering. They will develop open-source teaching materials—lectures, quizzes, tools, and tutorials—covering applications like molecule design, process optimization, and synthesis protocol generation using GenAI. These resources will first be piloted in TU Delft courses, and based on feedback, the team aims to extend their implementation across faculties. The project also includes community-building efforts, sharing insights to foster broader adoption of AI-driven education in the department.