Objectives

The third ECCOMAS Thematic Conference on Computational Science and AI in Industry (CSAI 2023) will be organized in Trondheim, Norway, 28-30 August, 2023. The first conference in this series were held in Jyväskylä, Finland, 12-14 June 2019. The second in 2021, in remote format.

The objective for CSAI 2023 is to be a meeting place for exploring the possibilities of computational sciences and artificial intelligence (AI) for solving future societal and economical challenges.

The advances in technology and the ever-growing role of digital sensors and computers in science have led to an exponential growth in the amount and complexity of (big) data that scientists and industries collect. Artificial Intelligence (AI) is getting closer and closer to Human Intelligence, and in the future, it has to be able to create the greatest value for all stakeholders: not only for the industry and users, but for the society as well. One great example where all actors benefit from the use of AI can be seen in healthcare.

Meanwhile, the data algorithmics of Computational Sciences are already improving performance and productivity in several industrial sectors. For example, the proliferation of sensors installed on complex systems at every level of industry help both to fine-tune service in real time and to regulate all production sequences at the highest possible level. While these principles are mainly applied in the industry, there is no reason why they would not work for society as well.

The knowledge of Computational Sciences should not ignore the knowledge of AI but has to benefit from its new technologies in a win-win alliance. While the impact of AI can provide a major competitive advantage for businesses and even for societal issues, Computational Sciences can provide new and innovative solutions for problem solving with algorithms boosted with the use of big data and AI. Together, these scientific fields have great potential to offer solutions not only to industrial issues, but also to the vast societal challenges of today.

This years CSAI will have a special emphasis on enabling technologies for Digital Twins, where we adopt the following definition of a Digital Twin [1]:

A digital twin is defined as a virtual representation of a physical asset, or a process enabled through data and simulators for real-time prediction, optimization, monitoring, control, and decision-making.

We will invite highly acknowledge scientists on this topic as Plenary and Keynote Lecturers as well as influential representatives from relevant industry.

[1] A. Rasheed, O. San, T. Kvamsdal. Digital Twin: Values, Challenges and Enablers from a Modeling Perspective. IEEE Access, 8:21980--22012, 2020, 2020.