Personal Health Interfaces Leveraging Human-Machine Natural Interactions

Objective

The goal of the PhilHumans (Personal Health Interfaces Leveraging Human-MAchine Natural interactionS) project is to train a next generation of young researchers in innovative Artificial Intelligence (AI) and establish user interaction with their personal health devices in an advanced and intuitive way. PhilHumans will investigate cutting-edge AI methods for human-machine interaction in the personal health domain through a well-designed and structured research training programme, with the aim to enhance EU firms competitiveness in the field for an effective and lasting market penetration in EU.
The research in PhilHumans will be performed by an intersectoral and multidisciplinary consortium consisting of 8 ESRs and a team of supervisors from the academic beneficiaries (University of Cagliari, University of Catania, University of Aberdeen, and Technical University of Eindhoven (TU/e)), the industrial beneficiaries (PHILIPS and R2M), and other external partners. The project will require the creation of a blend of interdisciplinary understanding of personal digital assistant, cognitive computing, (deep) machine learning, natural language generation & processing, advanced computer vision, and business development. The personal health areas that will be investigated are Mother&Child care, healthy-living and personal care, where the application of the proposed technology has promising potential.
All ESRs will enroll in a 3-years PhD research programme at beneficiary academic institutions. They are supposed to act as an integrated and complementary expertize team, whose aim is to tackle the fundamental challenge of combining heterogeneous data sources from multilingual speech/text processing and computer vision for improving conversation, detecting emotions, and improving social interactions. All the academic ESRs for at least 50% of their time will attend their secondment at PHILIPS, which will provide the required infrastructure and supervision by senior research staff.

Field of science

• /natural sciences/computer and information sciences/artificial intelligence/computer vision
• /natural sciences/computer and information sciences/artificial intelligence
• /natural sciences/computer and information sciences/artificial intelligence/machine learning

Programme(s)

• H2020-EU.1.3.1. - Fostering new skills by means of excellent initial training of researchers

Topic(s)

• MSCA-ITN-2018 - Innovative Training Networks

Call for proposal

H2020-MSCA-ITN-2018
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Funding Scheme

Coordinator

Participants (5)

Partners (10)