Digital technologies are transforming all sectors of our economy and will increasingly do so in the years to come. Thanks to the increasing capabilities of digital technologies, the next generation of smart industrial control systems (SICS) are expected to learn from streams of data and to take optimal decisions in real-time on the process at hand, leading to increased performance, safety, energy efficiency, and ultimately value creation.

Numerical optimization is at the very core of both learning and decision-making, since both the extraction of information from data and the choice of the most suitable action are naturally cast as optimization problems and solved numerically.

However, to realize this potential embedded learning and optimization methods needs to be developed, able to operate in industrial devices and to guarantee high safety standards.

ELO-X addresses the timely and pressing need for highly qualified and competent researchers, able to develop embedded learning- and optimization-based control methodologies for SICS, thus enabling new technologies and the next generation of digital industrial products and processes.

ELO-X is a Marie Curie Innovative Training Network (ITN) funded by the European Commission Horizon 2020 program. With 15 doctoral researchers working at 6 research universities and 5 international companies from 5 European countries, and further 5 partner organizations in the China, Japan and the US, ELO-X will accelerate research and development in embedded learning and optimization, delivering new methods and applications.

At the same time, the project will train skilled researchers able to further advance research and technology transfer of embedded learning and decision-making solutions to industry, reinforcing the EU technological leadership in strategic industrial fields such as transportation, energy, infrastructures, and manufacturing.