This graduate-level course focuses on advanced distributed ledger technologies (DLT) and applications. The students will be exposed to the latest DLT research trends and applications, including AI, IoT, connected vehicles, health, and complex supply chain applications. For example, advanced blockchain and AI applications in the connected vehicle domain can protect sensitive data associated with specific vehicles and drivers or enhance cooperative driving by securing and privatizing road information exchange and creating monetized incentives within the network of automated electric vehicles. Another example is the utilization of DLT in “shared manufacturing”, which relates to the economic driver of ’flexible production’. The course will also cover the utilization of DLT to support privacy protection in decentralized AI. The students will have the opportunity to improve their research, development, and presentation skills through the exposure to a set of challenging deliverables in the course

According to the examination regulation full attendance is intended for a PI. 80% attendance required to pass the course.

There will be three 5 evaluations (dates will be defined in the first lecture):

1. Individual research paper presentation (will be individually scheduled; 20 marks)
2. Project idea, abstract, and introduction (10 marks; minimum 3 references)
3. Project background/related work, research method, and preliminary results (20 marks; minimum 10 references)
4. Final project deliverable (40 marks; minimum 20 references)
5. Final project presentation (10 marks; minimum 20 references)