The goal of this doctoral project is to create visualization tools that help researchers analyze large-scale social-media text streams.
Study and develop novel visual analytics approaches for the interactive exploration and analysis of multilayer technological networks such as power systems.
Research use of immersive analytics for the visualization, exploration and analysis of the appearance and effect of extreme heat in Norrköping Municipality.
Deliver and study mature prototypes of AI Digital Assistants for the aviation domain, with a focus on Human-AI Teaming.
Design and evaluation of an interactive and explainable end-to-end Machine Learning (ML) lifecycle for industrial domain experts and end users.
Support the analysis of heterogeneous networks on multiple levels by novel visual representations and interaction techniques.
The purpose is to develop theory and tools for understanding human-automation collaboration within ATM.
The project studies self-explanatory automation for fighter aircraft through algorithms and design principles for more transparent interaction with highly automated systems.
Generic methods for visualization of complex situations to strengthen human-automation collaboration in real-time systems
Increase our understanding of unmanned traffic in cities, a future situation, and to explore new concepts for understanding and controlling traffic.
To develop and demonstrate concepts and technologies for safe integration both large and small Unmanned Aircraft Systems (UAS) into the airspace.
Design, prototype, and test concepts for Unmanned Traffic Management (UTM) for Dubai City in an interactive visualization and traffic simulation.
The project builds a physical and virtual infrastructure for Last Mile Delivery (LMDS).
Design and test an immersive and interactive exploranation of the drone flight between Linköping and Norrköping in Sweden.
To develop a Remote Operation Center (ROC), adapted for traffic-intensive archipelago traffic.
Visual analysis of (eventually dynamically changing) network structures together with attached multidimensional attributes.
Combining explorative mining and visual reasoning to facilitate progressive user-driven analysis of large and complex temporal event data sets.
Using visualization and AI to monitor and analyse behaviours of merchant ships in Swedish waters.
Interdisciplinary approaches for analyzing social networks and associated data for the problems of language use and variation.
Interdisciplinary WASP-DDLS project making use of visual analytics for enhancing quality and trust in genome-wide expression clustering and annotation.
The project models advanced air mobility in and near cities (AAM) for regional services in three regions, to understand how services that use larger and smaller drones can be made possible.
Assessing the potential of combining AI-based image processing and text mining with national impact-based weather warning systems.
Exploring the use of sonification as a mean for communication and public outreach activities.
Exploring the use of sonification to support visualization and visual data analysis.
The aim of this doctoral project is to explore how sonification can be used as a complement to visualization to perceptulize data.
Support the analysis of heterogeneous networks by novel visual representations and interaction techniques.
