AI and Robotics for Health and Rehabilitation

AI and machine learning (ML) have tremendous potential for improving the healthcare system by standardizing care across health providers while personalizing it to individual patients.

AI for Scientific Data Analysis

This theme is about utilizing the power of AI as a tool for scientific research. AI can be applied to, and potentially speed up, discovery and utilization in a variety of research disciplines, such as microscopy, physics, biology, chemistry, and astronomy.

Structured learning

This theme focuses on how to make use of structure in data to build machine learning (ML) and artificial intelligence (AI) systems which are safer, more trustworthy and generalize better. Structure includes the relationship between data, in time and space, and how the predictions change when data is transformed in specific ways, for example rotated or scaled. These topics are abstract and general but have a direct impact on the use of AI and ML in the sciences and in applications such as drugs and materials design, or medical imaging.

Chair themes

To see earlier theme events, click on "Calendar" above. Then use the "Show filter" button and filter the calendar by date.

<h3>CHAIR research tracks</h3>
The research themes are all hosted by one of CHAIR´s three research tracks – AI Foundations, AI for Science and AI Applications.

AI research has made tremendous strides and is being applied in countless systems. Yet, significant challenges remain in understanding and building AI systems which are general, reusable, efficient and safe. Reaching this goal requires fundamental advancements in machine learning algorithms and theory, mathematics and optimization, data science and statistics. Such research, with the potential to impact diverse application domains and areas of science, is represented in the track AI Foundations.

The natural sciences generate data of unprecedented volume through large-scale experiments and passive data collection. Here, AI has the potential to fundamentally change approaches to research, and speed up new discoveries and applications. At Chalmers, researchers in almost every department incorporate AI methods to discover patterns in such data, to produce testable hypotheses or to design future experiments. Research in the track AI for Science makes direct contributions to solve important problems in the natural sciences, through application and development of AI methods.

Impactful AI serves society. Towards this mission, Chalmers researchers develop and apply AI methods to solve domain-specific problems of high interest to private or public sectors, often together with external collaborators. The track AI Applications supports and highlights such research. Examples can be found within each of the Chalmers Areas of Advance: Energy, Health Engineering, Information &amp; Communication Technology, Materials science, Production and Transport.

CHAIR

Choose subject

[en: page.coursepage.titleprefix]

[en: page.courseslistingpage.filter.admissionlimithelptext]

[en: page.courseslistingpage.filter.inprogramplanhelptext]

[en: page.courseslistingpage.tooltipcontent]

Exam date for this course has changed from %s to %s.

See programme page at universityadmissions.se

Educational area

EU/EEA citizens are not required to pay fees​​.

[en: page.studyprogrammepage.subsview.title]

[en: page.studyprogrammepage.syllabusesview.acyearhelptext]

Current themes

CHAIR research tracks