The centre operates with SciTech projects, which are strategic research projects with the purpose of building up research and education capacity at the universities. Bridge projects, which are joint research/development/innovation projects between universities, companies, the public sector and GTS institutes with the purpose to increase the capacity of digitalisation and innovation for companies. Explore projects, which are small agile research projects with the purpose to quickly screen new ideas, and Educational projects, the aim of which is to support the master and PhD capacity building.
To teach many recent topics within digital technology at scale requires proper software infrastructures to support the teaching for lab exercises and projects. Some of these topics are data-driven systems, AI and cloud computing.
The mix of students in digital technology is low in diversity (e.g. female students). This is a problem on a societal level which also impacts the study environment.
Teaching quality and student feedback is negatively impacted by lack of teachers and many students. There is a need to consider how learning technologies can help improve teaching quality and student feedback both in physical and digital learning environments.
Artificial Intelligence brings the promise of technological means to solve problems that previously were assumed to require human intelligence, and ultimately provide human-centered solutions that are both more effective and of higher quality in a synergy between the human and the AI system than solutions that are provided by humans or by an AI system alone.
AI is radically changing society and the main driver behind new AI methods and systems is machine learning. Machine learning focuses on finding solutions for, or patterns in, new data by learning from relevant existing data.
AI is radically changing society and the main driver behind new AI methods and systems is machine learning. Machine learning focuses on finding solutions for, or patterns in, new data by learning from relevant existing data.
There is an unmet need for decentralised privacy-preserving machine learning. Cloud computing has great potential, however, there is a lack of trust in the service providers and there is a risk of data breaches.
Today, the manual visual inspection of grain is still one of the most important quality assurance procedures throughout the value chain of bringing cereals from the field to the table. In order to improve performance, robustness and consistency of this inspection, there is a need for automated imaging-based solutions to replace subjective manual inspection.
The mobility of people and things is an important societal process that facilitates and affects the lives of most people. Thus, society, including industry, has a substantial interest in well-functioning outdoor and indoor mobility infrastructures that are efficient, predictable, environmentally friendly,and safe.
The rapidly growing application of machine learning techniques in Cyber-Physical Systems leads to better solutions and products in terms of adaptability, performance, efficiency, functionality and usability.
Downtime of equipment is costly and a source of safety, security and legal issues. Today, organisations adopt a conservative schedule of preventive maintenance independent of the condition of equipment.
