EU Projects Office

The focus of SMARTHEP is a central question in a data-rich environment: how to make the most of the available data to take decisions fast and efficiently, making the most of the available data. The main purpose of SMARTHEP is to train a new generation of inter-sector researchers and give them the tools to tackle this challenge, by processing large datasets in real- time, aided by Machine Learning and hybrid computing architectures. The results of SMARTHEP will benefit the HEP community in providing cutting edge technology and algorithms for the area of data selection (triggering) and particle detection, leading to precise measurement of the fundamental constituents of matter and enabling the discovery of new physics processes.

Coordinator: ULUND, Sweden

Scientist in Charge from CERN:
Monica Pepe-Altarelli

Full costs of the project: 3.2 M€

EU funding: 3.2 M€

EU funding for CERN: 281 k€

RAISE

RAISE: AI- and Simulation-Based Engineering at Exascale

Compute- and data-driven research encompasses a broad spectrum of disciplines and is the key to Europe’s global success in various scientific and economic fields. The massive amount of data produced by such technologies demands novel methods to post-process, analyze, and to reveal valuable mechanisms. The development of artificial intelligence (AI) methods is rapidly proceeding and they are progressively applied to many stages of workflows to solve complex problems. Analyzing and processing big data require high computational power and scalable AI solutions. Therefore, it becomes mandatory to develop entirely new workflows from current applications that efficiently run on future high-performance computing architectures at Exascale. The Center of Excellence for AI- and Simulation-based Engineering at Exascale (AISee) will be the excellent enabler for the advancement of such technologies in Europe on industrial and academic levels, and a driver for novel intertwined AI and HPC methods. These technologies will be advanced along representative use-cases, covering a wide spectrum of academic and industrial applications, e.g., coming from wind energy harvesting, wetting hydrodynamics, manufacturing, physics, turbomachinery, and aerospace.

Coordinator: FZJ, Germany

Scientist in Charge from CERN: Maria Girone

Full costs of the project: 4.9 M€

EU funding: 4.9 M€

EU funding for CERN: 517 K€

1 January 2021 - 31 December 2023

hls4ml

hls4ml: High Level Synthesis for Machine Learning

With Deep Learning becoming ubiquitous in our life, running Deep Learning algorithms in real time on an heterogeneous set of hardware platforms is a pressing need in many aspects of our society. While traditional workflows based on standard CPUs and GPUs are established, Deep Learning inference on low-power devices (e.g., cars, smart phones, watches, etc) is gaining more attention. Typically, this would require strong background in electronic engineering to convert a neural network into a Digital Signal Processor. hls4ml proposes to develop a complete open-software library to automatically convert Deep Neural Networks to electronic circuits, using High Level Synthesis tools. With a large basis of potential applications (e.g., autonomous cars, medical devices, portable monitoring devices, custom electronics as in the real-time data processing system of large-scale scientific experiments, etc.), the hls4ml library would assists users by automatising the logic circuit design as well as by reducing resource utilisation while preserving accuracy.

Coordinator: CERN, Switzerland

Scientist in Charge from CERN:
Maurizio Pierini

Full costs of the project: 150 k€

EU funding: 150 k€

EU funding for CERN: 150 k€

1 April 2021 - 30 September 2022

Gamma MRI

Gamma MRI: the future of molecular imaging

Gamma-MRI will develop a clinical molecular imaging device based on the physical principle of anisotropic gamma emission from hyperpolarised metastable xenon. Gamma-MRI is a game-changer imaging technology, combining the high sensitivity of gamma ray detection and the high resolution and flexibility of MRI, bringing down by multiple fold the cost of molecular imaging. Six closely interlinked work packages will cover: production of hyperpolarised gamma-emitting xenon isomers; preserving hyperpolarisation until delivery to targeted organ; developing advanced image acquisition and reconstruction using physics- and artificial intelligence- based approaches; designing and assembling the prototype upon a low field versatile magnet; and implementing the first preclinical Gamma-MRI brain imaging experiment.

Coordinator: HES-SO, Switzerland

Scientist in Charge from CERN:
Magdalena Kowalska

Full costs of the project: 3.3 M€

EU funding: 3.3 M€

EU funding for CERN: 243 k€

1 April 2021 - 31 March 2024

NEWS

NEWS: NEw WindowS on the universe and technological advancements from trilateral EU-US-Japan collaboration

NEWS promotes the collaboration between European, US and Japanese research institutions in some key areas of fundamental physics. LIGO and Virgo collaborations have built the largest gravitational wave observatories and exploit the propagation of light and spacetime to detect gravitational waves and probe their sources. The Large Area Telescope (LAT) collaboration operates a gamma-ray telescope onboard the Fermi Gamma Ray Space Telescope mission and has revolutionized our view of the gamma-ray Universe. Fermi is the reference all-sky gamma-ray monitor for the follow-up searches for electromagnetic counterparts of gravitational wave sources. New-generation space telescopes will measure the polarization of X-rays from the cosmic sources and probe the laws of physics under extreme conditions of gravitational and electromagnetic fields. A complementary approach to probe the Universe is provided by particle accelerators built in laboratories. FNAL will provide the cleanest probes for physics beyond the Standard Model of particle physics. The Muon (g-2) experiment will measure the muon anomalous magnetic moment with unprecedented precision. Mu2e will search for the neutrinoless coherent muon conversion to an electron in the Coulomb field of a nucleus, which would be the unambiguous evidence of new, unknown, physics. These endeavors require innovative detectors and cutting-edge technologies that NEWS will develop to open new “windows” in fundamental physics.

Coordinator: INFN, Italy

Scientist in Charge from CERN:
Marzio Nessi

Full costs of the project: 1.5 M€

EU funding: 1.5 M€

EU funding for CERN: 54 k€

1 July 2017 - 31 June 2021

I.FAST

I.FAST: Innovation Fostering in Accelerator Science and Technology

Particle accelerators currently face critical challenges related to the size and performance of future facilities for fundamental research, to the increasing demands coming from accelerators for applied science, and to the growing applications in medicine and industry. The I.FAST project aims to enhance innovation in the particle accelerator community, mapping out and facilitating the development of breakthrough technologies common to multiple accelerator platforms. The project will involve 49 partners, including 17 industrial companies as co-innovation partners, to explore new alternative accelerator concepts and advanced prototyping of key technologies. These include, among others, new accelerator designs and concepts, advanced superconducting technologies for magnets and cavities, techniques to increase brightness of synchrotron light sources, strategies and technologies to improve energy efficiency, and new societal applications of accelerators.

Coordinator: CERN, Switzerland

Scientist in Charge from CERN:
Maurizio Vretenar

Full costs of the project: 18.6 M€

EU funding: 10 M€

EU funding for CERN: 2. 9 M€

1 May 2021 - 30 April 2025

BiCIKL

BiCIKL: Biodiversity Community Integrated Knowledge Library

BiCIKL is a proposal that will initiate and build a new European starting community of key research infrastructures, establishing open science practices in the domain of biodiversity through provision of access to data, associated tools and services at (1) each separate stage of, and (2) along the entire research cycle. BiCIKL will provide new methods and workflows for an integrated access to harvesting, liberating, linking, accessing and re-using of sub-article-level data (specimens, material citations, samples, sequences, taxonomic names, taxonomic treatments, figures, tables) extracted from literature. BiCIKL will provide for the first time access and tools for seamless linking and usage tracking of data along the line: specimens → sequences → species → analytics → publications → biodiversity knowledge graph → re-use.

Coordinator: Pensoft

Scientist in Charge from CERN:
Jose Gonzales

Full costs of the project: 5 M€

EU funding: 5 M€

EU funding for CERN: 137 k€

1 May 2021 - 30 April 2024

Subscribe to