by Tove Kvarnström | Feb 28, 2023
PI: Joachim Rodrigues (LU); co-PI: Oscar Gustafsson (LiU) A promising technique to boost performance and energy efficiency in data-centric computing architectures is the integration of computation logic in the near proximity of on-chip memory. In this project, we...
by Tove Kvarnström | Feb 28, 2023
PI: Richard Pates (LU); co-PI: Anders Hansson (LiU) Many classical optimal methods for estimation and control have provable robustness and performance guarantees that can enhance the sustainability and resilience of engineering systems. However, their implementation...
by Tove Kvarnström | Feb 28, 2023
PI: Viktor Larsson (LU); co-PIs: Mårten Wadenbäck (LiU), Michael Felsberg (LiU) This project concerns 3D mapping methods which are used to enable re-localization and navigation in large-scale environments. In particular, we will focus on sparse reconstruction methods...
by Tove Kvarnström | Feb 28, 2023
PI: Christian Gehrmann (LU); co-PI: Mikael Asplund (LiU) The huge amount of cellular connected devices can be used to launch Distributed Denial of Service (DDoS) attacks which are a severe threat against telecommunication infrastructures and services. The new analytic...
by Tove Kvarnström | Feb 28, 2023
PI: Amir Aminifar (LU); co-PIs: Christoph Kessler (LiU), Petru Eles (LiU) The new generation of artificial intelligence (AI) and machine learning (ML) techniques have recently been shown to require non-negligible energy for both training and inference. FL4IoT will...
