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: Andreas Kerren (LiU); co-PI: Richard Pates (LU) Multilayer networks are a relatively new way to model complex real-world systems that demand novel and efficient solutions for their analysis. Especially when regarding large and heterogeneous data typically used in...
by Lena Tasse | May 3, 2021
PI: Claudio Altafini (LiU). Co-PIs: Anders Rantzer (LU), Erik G. Larsson (LiU). The overall goal of this project is to interface control systems and network science methodology, with the purpose of investigating the following specific topics: developing network-level...
by Lena Tasse | May 3, 2021
PI: Anders Rantzer (LU). Co-PIs: Richard Pates (LU), Claudio Altafini (LiU), Anders Hansson (LiU). This project aims to develop scalable algorithms to monitor, predict, and analyze data from large-scale dynamic networks. In line with ELLIIT focus theme Big Data and...
by Lena Tasse | May 3, 2021
Krzysztof Bartoszek, LiU and Niklas Wahlberg, LU Graph learning is an important topic in science and technology. In this project we will develop new methods for tree-structured graphs, motivated by phylogenetics but with potential use in other network-based...
