15 April 2024

How can artificial intelligence, AI, improve, for example, health care and local and national public transport? A research group at LiU is working to develop AI for the benefit of society.

Head shot of a smiling man wearing glasses and a blue shirt
Postdoc Mattias Tiger is part of the research group ReaL (Reasoning and Learning) at the Division of Artificial Intelligence and integrated Computer Systems, which is part of the Department of Computer and Information Science. Charlotte Perhammar

The LiU researchers use hybrid AI, an approach that combines different methods from the AI field such as machine learning, reasoning and planning. In this way, they create practically useful systems for specific operations.

Charlotte Perhammar

“We figure out how to implement safe and robust AI systems that work in real life and are reliable,” says postdoc Mattias Tiger. 

Many stakeholders want to collaborate with the research group. For example, the researchers have looked at how new AI systems can support several of Region Östergötland’s operations, including health care. The group is also collaborating with the public transport provider Östgötatrafiken and has improved the punctuality of their buses. Current estimated arrival times originate from previous projects where they made major improvements using machine learning. The researchers also have ongoing collaboration projects with the Swedish Transport Administration to improve arrival and departure time estimates for all rail traffic in Sweden. The results have been good, and the research group is now supporting the Swedish Transport Administration in moving the forecast models to production. 

A research project with Saab and Ericsson is about coordinating a large number of low-flying objects in society and the safety aspects this would entail. The task of such an object can be to deliver packages, collect inspection data on things such as heat loss in a house or make a three-dimensional map for self-driving vehicles.

Charlotte Perhammar
Mattias Tiger and his colleagues also help large global logistics companies save significant amounts of carbon dioxide by ensuring that ships travelling between, for example, Asia and Europe do not run empty unnecessarily.

 

The article is also published in LiU magasin.

Contact

ReaL (Reasoning and Learning)

Postdoc Mattias Tiger is part of the research group ReaL (Reasoning and Learning) at the Division of Artificial Intelligence and integrated Computer Systems, which is part of the Department of Computer and Information Science. ReaL also supports organisations in taking digitalisation work further, becoming more data-driven and being able to take advantage of AI.

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