Artificial intelligence (AI) and machine learning (ML) are pushing scientific research into new domains, providing new opportunities to answer the complex societal and economic challenges facing our societies. From understanding the universe to tracking how viruses infect humans, producing large-scale scientific research requires increasingly innovative AI and ML, both for the running of cutting-edge scientific instruments and for the complex analysis of large amounts of data.
On 28 April 2022, the EIROforum alliance of European scientific infrastructures, CERN, ESO, ESA, EMBL, ESRF, ILL, European XFEL and EUROFusion will hold a conference focusing on the grand challenges in AI and data science. Hosted at the EMBL Heidelberg, with a free live streaming option for virtual participants, the conference will include workshops and talks presenting leading data science and AI from the EIROforum members, and explore how they can contribute to scientific progress with societal and economic impact.
Conference Chair, Director of EMBL-EBI and Deputy Director General of EMBL Ewan Birney explains: “Europe’s shared scientific infrastructures include the world’s best – from particle accelerators recreating the earliest moments of the Universe, to telescopes able to detect the earliest light in that Universe, and from research facilities unlocking the inner workings of cells to understand how life works on this planet, to satellite platforms able to examine the entire planet at macro and micro scales. As world leaders, we were quick to recognise the importance of data, analysis and artificial intelligence across all our diverse sciences, and the transformative impact these developments will have on science and on society. This conference will bring together the leaders in the field alongside policy makers, and stimulate further discussion on how to harness our access to large-scale scientific data with artificial intelligence, and thus help Europe thrive now and in the future.”
Simone Campana, CERN
“Our infrastructures share the common challenge to collect, analyse and curate large volumes of scientific data. The novel methodologies and experience we acquired for this purpose present a solution for the needs of other sectors and society at large.”
Tim Smith, CERN
“Openly sharing data, technologies and infrastructure is common place in science as it enables us to build on the findings and creations of others, advancing everyone. What works for science’s grand challenges can empower society as well, as the basis for fact-based decision making.”
Andreas Kaufer, ESO
Vincent Favre-Nicolin, ESRF
“All major research infrastructures are faced with ‘big data’ challenges – to process increasing amounts of data both faster and smarter, and to provide the results to users in the most efficient and durable way. The infrastructure, algorithmic and social aspects are very similar across all EIROforum members, and this conference will be an excellent opportunity to gain a wide overview.”
João Figueiredo, EUROFusion
“In modern science, the challenges of distributing, processing and analysing vast amounts of data is of paramount importance to optimise and fully profit from the research carried forward using the infrastructures of the largest scientific organisations. The sharing of the combined know-how of the EIROforum members in data science and the applications of artificial intelligence, used in telescopes and microscopes, in fusion reactors and space satellites, is certainly of great interest.”
Paolo Mutti, ILL
“AI and ML are everywhere nowadays, in our connected objects, telephones and even at the hospital. The benefit of these techniques have started to enter the scientific world as well, but their potential has still to be fully exploited. Great advantages can be achieved in the way scientists perform experiments and in the quantity and quality of information that can be extracted from the measured data. This EIROforum event is a great way to exchange practices between the different partners to move forward in exploring the new opportunities offered by AI.”