SMARTHEP: Synergies between Machine leArning, Real Time analysis and Hybrid architectures for efficient Event Processing and decision making

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€