Artificial intelligence (AI) is transforming the way we engage with science, engineering, and design—impacting the entire problem-solving process. AI is no longer just a tool but an integral part of developing hypotheses, designing experiments, optimizing products, and enhancing creativity through generative methods. At TU Delft, we strive to equip students for this reality, recognizing that AI knowledge is becoming increasingly essential across every discipline.
This means more than simply offering general AI literacy; it involves directly integrating AI education into each discipline. AI applications vary widely: from generating floorplans in architecture to molecular engineering in chemistry. This diversity in applications requires students to learn how to work with AI in ways specific to their own discipline. By embedding AI education within the discipline, we strengthen students' knowledge and skills, enabling them to use AI responsibly to address complex challenges in their work. With this approach, TU Delft prepares graduates for a future where AI is an inseparable part of their professional practice.
CALL FOR PROPOSAL ON AI-AUGMENTED ENGINEERING
To prepare future engineers from all disciplines at TU Delft and skill them in AI-augmented design, engineering and science, our students could benefit from education on how to work with AI-augmented techniques, and apply these in a responsible way.
The TU Delft AI-Initiative makes 4 grants of 25k€ each available, to stimulate the acquisition of knowledge and skills about AI-augmented engineering education and to share this with other teachers at TU Delft.
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)
The TRUGEN project, led by Riccardo Taormina and Iuri Rocha, explores the integration of Generative AI in Civil Engineering and Geosciences (CEG) education to help students develop proficiency in responsible GenAI use. The team piloted the project in the CEGM2003 module (Data Science and Artificial Intelligence for Engineers, 10 EC), followed by approximately 50 Master’s students across three programs. New teaching materials were developed to guide students in prompting LLMs effectively, using GenAI for pair programming, retrieving information from a knowledge base, and drafting poster presentations. A post-course survey showed that students rely on GenAI for coding and to deepen their understanding of the course material, though they remain cautious about its use.
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. Their student assistants are busy documenting the use of GenAI in design courses and interviewing Delft graduates about the role of GenAI in professional design practice. Meanwhile, they have been hosting several events to build the AI & design community at TU Delft. At these events, they discussed challenges and opportunities of LLMs in programming education and shared how to use new tools like ChatGPT Canvas, Cursor and Bolt.new. They also demonstrated how to use GenAI for physical computing with Arduino, how to create a specialised chatbot powered by the ChatGPT API and how to integrate multiple elements together into a digital product experience. More events like this, whereby also industrial partners will be involved, are scheduled, so stay tuned!
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. The project is progressing toward integrating generative AI into chemical engineering education. After initial discussions, the team has outlined a framework for incorporating GenAI into two courses: (1) the computational practical (a mandatory numeric course for chemical engineering master students) and (2) the elective AI for (bio)-chemical engineering. They are developing lectures, quizzes, interactive tools, and corresponding assignments. A demonstrator for GenAI in engineering design is at the core of this project. The team is also engaging with broader academic and industry communities to expand adoption. Future efforts will focus on integrating computational tools for GenAI into chemical engineering education.
Fostering Critical AI Literacy: trustworthiness, confidence, and responsible use of AI in Nanobiology education
Led by Arjen Jakobi, this project aims to teach Nanobiology students at TU Delft how to responsibly use AI in scientific research. It focuses on the identifying limitations of AI, such as overconfidence and the potential for misleading results, and helps students develop skills to critically assess AI outputs. Students will gain hands-on experience with AI tools used in scientific research, learning how to interpret, validate, and use AI responsibly. The goal is to equip our students with a critical AI literacy that fosters trustworthiness, confidence, and responsible practices for the application of AI in scientific work.
Safe, Reliable, and High-quality, AI-Augmented Materials Science and Engineering
The project led by Kevin Rossi, Sid Kumar, and Martina Vittorietti, will target the development of educational material on artificial Intelligence for materials design and understanding, with a focus on equipping students with the ability and attitude to critically evaluate generative AI results.
To this end, educational material will cover topics ranging from regression, bias-variance trade-off, cross-validation, and uncertainty estimation to generative AI and LLMs, and numerous case-studies relevant to materials science and engineering. Dissemination efforts involve workshops, publications, and collaborations to share best practices, ensuring the responsible and effective integration of AI into materials science education.
Future-Proofing Designers with AI-Augmented Design Education
Evangelos Niforatos aims to integrate AI tools into design education at IDE to enhance collaboration between designers and AI. The project focus will be on concept development, iterative prototyping, and user-centered AI integration. They will leverage new MSc electives, with core GenAI components, as field labs to experiment with AI-powered design methods, including LLMs, VR/XR, and synthetic personas. Key outcomes include AI-augmented teaching principles, open-source tutorials, and a repository of design techniques. The goal is to prepare future designers for AI-driven industries through interdisciplinary collaboration and hands-on learning.
Practical AI in Engineering: A Case-Study-Driven Open Repository and Course
This project led by Barah Abdi aims to bridge the gap between AI/ML technical skills and their critical real-world application. An open repository of interactive AI case studies and a course that guides students through defining AI problems with industry, assessing data integrity, interpreting AI outputs, and considering ethical implications will be developed. Co-created with industry professionals, these resources will equip students with practical tools for model evaluation and decision-making. Open to various disciplines, the materials will be freely accessible, fostering a deeper, hands-on AI learning experience.
Symposium on AI education
A line-up of interesting keynotes and workshops about AI Education captivated the audience during the fourth annual Spring Symposium organised by TU Delft AI Initiative. From the fields of law and architecture to physics – a variety of disciplines were discussed, each showing how AI is a game changer for the future of their respective fields and the consequences this has for the education of the future. This underscores the importance of considering AI education across the whole university.
MOOC: AI in Architectural Design
To prepare the architect of the future, we’ve developed a new MOOC: AI in Architectural Design. This free course offers the opportunity to stay ahead in the evolving world of design and technology, and is not only interesting for practicing architect but also for students who are eager to diversify their skills, enhance their design process and boost their job market competitiveness. The course challenges to rethink design as data storytelling by leveraging AI, machine learning, and computer vision. The duration of the MOOC is 10 weeks (2-4 hours per week), and even though the course is free it allows you to earn a certificate (for $149).
The instructors are Seyran Khademi (Assistant Professor at Faculty of Architecture and the Built Environment TU Delft & co-director of AiDAPT Lab), Casper van Engelenburg (PhD candidate at TU Delft), and Pablo G. Morato (Postdoc at TU Delft).
What you’ll learn in short:
• Understand AI and machine learning as the science behind the technology.
• Explore computer vision and its applications in architectural design.
• Master data storytelling to upgrade your design presentations.
• Gain practical experience with Python and build your own small machine learning project.
