Big data and AI
Big data and AI
The researchers are studying different techniques for handling large amounts of data from a technical perspective with regard to, for example, storage and database systems as well as how AI, machine learning and information mining can be used for pattern recognition and trends in large amounts of data.
At BTH there is a research environment in big data with funding from the Swedish Knowledge Foundation. The research focuses on creating resource efficient systems for the analysis of large amount of data. The research is conducted in cooperation with a number of companies including Ericsson, Telenor and Sony Mobile Communications.
Research environment BigData@BTH
Data will be generated at an ever-increasing rate for the foreseeable future. Added value and cost savings can be obtained by analyzing big data streams. The analysis of large data sets requires scalable and high-performance computer systems. In order to stay competitive and to reduce consumption of energy and other resources, the next generation systems for scalable big data analytics need to be more resource-efficient. The research profile, Scalable resource-efficient systems for big data analytics, combines existing expertise in machine learning, data mining, and computer engineering to create new knowledge in the area of scalable resource-efficient systems for big data analytics. The value of the new knowledge will be demonstrated and evaluated in two application areas (decision support systems and image processing).
The needs and interests of our 9 industrial partners are grouped into industrial challenges. Based on these challenges and in cooperation with our partners we have defined initial sub-projects grouped into four research themes:
Research theme A: Big data analytics for decision support
Research theme B: Big data analytics for image processing
Research theme C: Core technologies (machine learning)
Research theme D: Foundations and enabling technologies
Funder: KK-stiftelsen 2014-2020
Partners: Arkiv Digital AD, Compuverde, Contribe, Ericsson, Indigo IPEX, Noda Intelligent Systems, Telenor Sverige, Sony Mobile Communications, and Maingate Enterprise Solutions
Contact: Håkan Grahn, firstname.lastname@example.org