Today, there are many compute- and memory-hungry data-intensive workloads from big data analytics applications to deep learning. These workloads increasingly run on shared hardware resources, which requires building hardware resource managers that can both serve the needs of workloads and utilize hardware well. Predicting the resource utilization of applications can aid such resource managers …
Supervisors: Pınar Tözün, Ehsan Yousefzadeh-Asl-Miandoab
Semester: Fall 2022
Tags: benchmarking, hardware resource consumption estimation, machine learning

The Danish Student Cubesat Program is an inter university collaboration that will launch 3 cubesats into Low Earth Orbit over the next 4 years. The satellites will be designed, operated, programmed and built by students and the project offers an opportunity for Master’s students to take part in a live satellite project. ITU is partnering with Aarhus University on DISCOSAT2 which will be an …
Supervisors: Sebastian Büttrich, Julian Priest
Semester: Fall 2021
Tags: Satellite, Cubesat, Image processing, Machine Learning, edge, constrained computing

Machine learning is used extensively in different applications, including medical imaging and natural language processing. As different types of data are involved, it is reasonable to assume that different methods are needed for each application. However, there are also opportunities in translating a method successful in one application, to the other application where it is not widely used. The …
Supervisors: Veronika Cheplygina
Semester: Fall 2021
Tags: machine learning, natural language processing, medical imaging, literature review

Machine learning algorithms for skin lesion classification typically learn from images which have been labeled as malignant (for example, melanoma) or not. Such tasks can still suffer from overfitting due to limited dataset size. In other computer vision tasks, crowdsourcing labels has been effective, but the average person typically does not have the background to classify skin lesions. However, …
Supervisors: Veronika Cheplygina
Semester: Fall 2021
Tags: machine learning, medical imaging, crowdsourcing, similarity

ITU is a partner in the Danish Student Cubesat Program, DISCO which will launch a series of small satellites into orbit, starting with DISCO 1 in 2023 and followed by DISCO2 in 2024. As part of this project ITU is installing a satellite ground station with a range of antenna rotators on the roof of Rued Langaards Vej building and the equipment has been purchased. The ground station will track the …
Supervisors: Julian Priest
Semester: archive
Tags: Satellite, Image processing, Edge, Constrained Computing, Networks, Machine Learning, Embeded, Software Defined Radio

ITU is a partner in the Danish Student Cubesat Program DISCO, which will launch a series of small satellites into orbit, starting with DISCO 1 in 2023 and followed by DISCO2 in 2024. ITU is developing a hi-res multi camera imaging payload for earth observation primarily in the Arctic. We are developing an on satellite machine learning capability using an ML coprocessor, as well as models that can …
Supervisors: Julian Priest
Semester: archive
Tags: Satellite, Image processing, Edge, Constrained Computing, Networks, Machine Learning, Embeded, Radio

For this project, you would be working with a partner company who are looking to re-establish wood as a building material for sustainable architecture, and thus are using sensors for quality control - to detect damages and deterioration in buildings. Wood such as timber may be analyzed by non-intrusive acoustic impact testing and subsequent waveform analysis, and the expectation is that machine …
Supervisors: Sebastian Büttrich
Semester: Fall 2021
Tags: IoT, sensors, machine learning, acoustics

There is currently a lot of progress in really small, yet powerful visual machine learning / computer vision, on hardware like the OpenMV Cam H7, Arduino Portenta Vision Shield, Luxonis LUX-ESP32, Himax WE-I Plus, Arducam Pico4ML, and Raspberry Pi, and on software platforms such as TinyML or OpenMV IDE. While many popular use cases stem from fields like traffic analysis, wildlife monitoring, we …
Supervisors: Sebastian Büttrich
Semester: Fall 2022
Tags: IoT, sensors, machine learning, computer vision

The goal of the project is to explore the accuracy of electricity production predictions based on historical data and weather predictions. This may be tackled as a sequence prediction problem using recurrent neural networks The long term goal is to incorporate wind turbines in the reserve market for electricity.
Supervisors: Philippe Bonnet, Sebastian Büttrich
Semester: Fall 2019
Tags: Wind Energy, Energinet, Forecasting, Machine Learning, Deep Learning