Digital Twin Engineering

Course manual 2025/2026

Course content

In this course, students will become familiar with the concept of digital twins and will learn and practice all aspects of engineering such a system. Students will learn about the typical data sources for such a system, different approaches to model the environment and existing modelling techniques, ways to integrate physical constraints and behaviours into the virtual model, communication mechanisms and protocols, data flows, streaming and messaging, real-time data processing and analytics. They will analyse the role of AI in digital twins, look into ways to validate the fidelity of a digital twin system with respect to its physical counterpart and discuss future trends and ethical aspects of digital twin technologies.

From a practical perspective, the students will develop their own digital twin of a sensor-rich environment. They will investigate a specific use case, using publicly available sensor datasets, construct their own digital representation model of a physical environment, develop a communication mechanism to efficiently process incoming sensor readings, and demonstrate the ability of the digital twin to adapt to changes in the physical environment in real-time.

Study materials

Other

• The reading materials will consist of a collection of recent scientific articles and other online material on the topic.

Objectives

• Understand and be able to explain digital twin concepts.
• Be familiar with and be able to apply all aspects of a digital twin system, including identifying and analysing diverse data sources, applying diverse modelling and simulation techniques, processing real-time data.
• Be able to design, model, and program a digital twin system that makes use of a variety of data sources.
• Be able to validate the fidelity of a digital twin.
• Gain familiarity with the latest research publications and be able to participate in scientific discussions on the topic.

Teaching methods

• Lecture
• Seminar
• Presentation/symposium
• Self-study
• Working independently on e.g. a project or thesis
• Supervision/feedback meeting

Learning activities

Attendance

Additional requirements for this course:

The course requires strong programming skills and understanding of modelling concepts and methodologies.

Assessment

The final grade is based on the seminar presentation and participation, the group project, and the final exam.

Assignments

Group-based seminar, presenting and discussing a relevant scientific article

Group-based project on creating a digital twin

Final exam

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Contact information

Coordinator

• Victoria Degeler

Lecturer: Victoria Degeler, v.o.degeler@uva.nl

Teaching Assistant: Imane El Ghabi, i.elghabi@uva.nl