Multimodal Data Processing of Earth Observation Data

Based on observations of the Earth, a range of Danish public organizations build and maintain important data foundations that are used for decision-making, e.g., for executing environmental law or making planning decisions in both private and public organizations in Denmark. This project aims to support the digital acceleration of the green transition by strengthening the data foundation for environmental data.

Hardware/software Trade-off for the Reduction of Energy Consumption

Computing devices consume a considerable amount of energy. Implementing algorithms in hardware using field-programmable gate arrays (FPGAs) can be more energy efficient than executing them in software in a processor. This project explores classic sorting and path-finding algorithms and compare their energy efficiency and performance when implemented in hardware.

HERD: Human-AI Collaboration: Engaging and Controlling Swarms of Robots and Drones

Today, robots and drones take on an increasingly broad set of tasks. However, such robots are limited in their capacity to cooperate with one another and with humans. This project aims to address multi-robot collaboration and design and evaluate technological solutions that enable users to engage and control autonomous multi-robot systems. 

Mobility Analytics using Sparse Mobility Data and Open Spatial Data

The amount of mobility-related data has increased massively which enables an increasingly wide range of analyses. When combined with digital representations of road networks and building interiors, this data holds the potential for enabling a more fine-grained understanding of mobility and for enabling more efficient, predictable, and environmentally friendly mobility.

Verifiable and Safe AI for Autonomous Systems

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. However, cyber-physical systems are often safety critical, e.g., self-driving cars or medical devices, and the need for verification against potentially fatal accidents is of key importance.