Monica Caballero

R+D Project Manager, Everis

Monica Caballero is a Project manager within the Supported Smart Innovation (SuSI) unit in everis, promoting and coordinating European projects mostly in the ICT sector. She obtained her Ph.D. with honours in Signal Theory and Communications from the Polytechnic University of Catalunya (UPC) in 2009. She also owns a Master in Business Innovation (UPC, 2016). Monica gained experience in R+D in the private sector working for three years on speech recognition and machine learning areas. After that she worked for 9 years on the European Programmes unit of the technology centre Eurecat until 2019 when she joined everis. In everis, she is acting as project coordinator and promoting the participation of everis in EU funded projects as well as leading and participating in the creation of new project proposals in the ICT domain. In the last 10 years she has been working around European tenders. She has participated in more than 20 several European and national research projects related to ICT applied in different industries, and has played an active role in different relevant associations in the ICT and media sectors (NEM – Member of the Advisory Board). As a project manager, she successfully coordinated 2 FP7 and 2 H2020 projects and is currently coordinating the project DeepHealth with a Consortium of 22 partners working around AI, Big Data and HPC aspects. She is an active member of the BDVA association and its working group around AI and Health.

Monica is speaking at

Application Track 2 - Health
November 4, 2020
12:00 pm - 1:30 pm



This session gives a high level view of AI in Healthcare whitepaper written by Healthcare subgroup, Application Task Force of BDVA. The whitepaper gives a viewpoint of European stakeholders on AI in healthcare. It documents the outcome of a literature study, online survey and a physical workshop with healthcare experts of BDVA community covering academia, industry and government.

During the webinar, the following topics will be addressed:
  • Importance and key areas of AI in Healthcare
  • Technical and non-technical challenges
  • Enablers, vision and future potential of AI in Healthcare
  • Successful use cases

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