by Bernd Zwattendorfer, Stephan Krenn and Thomas Lorünser

CREDENTIAL is an EU H2020 funded research project that is developing, testing, and showcasing innovative cloud-based services for storing, managing, and sharing digital identity information and other highly critical personal data with a demonstrably higher level of security and privacy than other current solutions. This is achieved by advancing novel cryptographic technologies and improving strong authentication mechanisms.

by Daniel Slamanig, Agi Karyda and Thomas Lorünser

The EU Horizon 2020 PRISMACLOUD research project is dedicated to enabling secure and trustworthy cloud-based services by improving and adopting novel tools from cryptographic research.

by Beatriz Gallego-Nicasio Crespo, Melek Önen and Ghassan Karame

The main goal of the TREDISEC project is to increase trust in cloud technology by providing solutions that enhance data security and provide strong privacy guarantees, without hampering the efficiency-and-reduced-cost attractiveness of existing cloud systems.

by Daniele Spoladore, Gianfranco Modoni and Marco Sacco

An ontology based approach that aims at enhancing interoperability between home devices and services is being developed by the Italian “Design For All” research project.

by Christoph Trattner, Tomasz Kuśmierczyk and Kjetil Nørvåg

Food is a central part of our daily lives and is one of the most important factors that shape our health and well-being. Although research on individual food preferences has existed as a well-established field of study for several decades, there has been very little attention devoted to understanding recipe consumption and production patterns on the World Wide Web. To contribute to knowledge in this area, we recently initiated “FOODWEB”, a research project that studies traces of users online with the goal of better understanding how we consume and produce food.

by Maria Koskinopoulou and Panos Trahanias

Imitation learning, which involves a robot observing and copying a human demonstrator, empowers a robot to “learn” new actions, and thus improve robot performance in tasks that require human-robot collaboration (HRC). We formulate a latent space representation of observed behaviors, and associate this representation with the corresponding one for target robotic behaviors. Effectively, a mapping of observed to reproduced actions is devised that abstracts action variations and differences between the human and robotic manipulators.

by Costas Bekas

“Mantle convection” is the term used to describe the transport of heat from the interior of the Earth to its surface. Mantle convection drives plate tectonics – the motion of plates that are formed from the Earth’s crust and upper mantle – and is a fundamental driver of earthquakes and volcanism. We modelled mantle convection using massively parallel computation.