Maja conducts research into green algorithms: All projects count
15 June 2023
Maja Hanne Kirkeby is Associate Professor at Roskilde University (RUC) and works closely with companies and other researchers to develop more energy efficient software solutions.
Intelligent technology must help prevent a repeat of the floods of 2011 and 2013
13 April 2023
Denmark must prepare for more extreme weather in the future. By using machine learning and artificial intelligence, researchers will effectively be able to prevent floods.
Climate change: We need to act now, and we need help from digital technology
28 March 2023
A recent report from the Intergovernmental Panel on Climate Change is full of distressing reading. Digital development must speed up, and researchers can play a leading role in the development of digital solutions to counteract climate change.
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.
