The Alan Turing Institute and FCAI developing Virtual Laboratories and more in wide-ranging collaboration
The Alan Turing Institute and the Finnish Centre for Artificial Intelligence (FCAI) are actively building out their partnership. Both institutions are working on harnessing data science and artificial intelligence to accelerate science and develop and apply new AI methods to challenges in domains such as healthcare.
Photo: Yuri Arcus
FCAI and The Alan Turing Institute signed a memorandum of understanding (MoU) in March 2019, formally establishing a partnership between the two organisations. Many of the researchers have worked together for a long time, but the MoU makes the collaboration more transparent and formal.
“Having the MoU made it very easy to approach the collaborators and get the work started, without establishing externally funded research projects,” says Associate Professor Arto Klami from the Department of Computer Science at the University of Helsinki.
Klami himself is involved in two different collaborations: one on the fundamental question of statistical inference and improving computational efficiency by accounting for the geometry induced by models, and another on Virtual Laboratories.
A Virtual Laboratory is an environment for accelerating the process of research and development, for example for drug design or material physics research, through a combination of physical and simulated experiments.
One of the goals of FCAI is to develop tools for AI-assisted decision-making, design and modeling, but being able to do this requires the research environment to be fully digital, with capability for example to simulate the results of hypothetical experiments.
“The Turing, in turn, has extensive experience on digital twins, which are essential building blocks of such a digital environment, and by combining these we were able to formalize the concept of an AI-assisted Virtual Laboratory,” says Klami.
Shared goals
The scientific and societal goals of the Turing and FCAI are very similar and now the two institutions can better advance them together. Both institutes also include and collaborate with a broad range of scientists in other disciplines in pursuit of better AI solutions.
Thanks to collaboration it is now easier to identify cases where AI techniques developed at one institute could help other scientific domains at the other.
Researchers at both institutions have also been working on increasing the visibility of these opportunities.
“This is important especially because the Turing is a really broad organization. Much of the current collaboration is with their data-centric engineering programme, but we are eager to extend the collaboration also to other research programmes,” says Klami.
Kickstarting a new collaboration
For individual researchers the formalized partnership makes is easier to kickstart new collaborations.
“For example, research visits in either direction can be easily arranged and we can contact liaisons at the Turing to help identify the right collaborators, for example for EU projects. On a higher level, the partnership increases the impact of what we do and say,” says Klami.
All collaboration between FCAI and the Turing is welcome under the MoU umbrella.
“If an FCAI member already has ongoing collaboration or a collaborator in mind and needs, for example, funding for a research visit to plan the project, then they can use the HIIT funding form to apply. Just remember to mention that your request relates to the partnership and explain how it aligns with the FCAI goals,” says Klami.
If you would like to find collaborators for your own research, or you have a collaborator at The Alan Turing Institute but they are not aware of the partnership, you can contact Arto Klami.