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Universities, R&D Groups and Academic Networks

CLOSER is a unique forum for universities, research groups and research projects to present their research and scientific results, be it by presenting a paper, hosting a tutorial or instructional course or demonstrating its research products in demo sessions, by contributing towards panels and discussions in the event's field of interest or by presenting their project, be it by setting up an exhibition booth, by being profiled in the event's web presence or printed materials or by suggesting keynote speakers or specific thematic sessions.

Special conditions are also available for Research Projects which wish to hold meetings at INSTICC events.

Current Academic Partners:


CloudLightning is a 36-month H2020 project to develop an intelligent, power-efficient cloud computing infrastructure that will provide energy savings to cloud service providers and simplify access to cloud resources for cloud consumers.

ESTG (School of Management and Technology)

Founded in 1999, ESTG (School of Management and Technology) is a dynamic and proactive institution of higher education integrated in Porto Polytechnic (IPP). The institution’s mission is to take part in development, social wellbeing, and technical and scientific national excellence, by promoting a solid education, enabling students to become innovative leaders of progress and innovation. ESTG involves about 1300 students distributed by multiple BSc and MSc degrees concerning 4 main areas: Computer Science, Business Sciences, Legal Practice and Occupational Safety and Quality. 


RECAP is a 36-month H2020 project to develop the next generation of cloud, edge and fog computing capacity provisioning via targeted research advances in cloud infrastructure optimisation, simulation and automation.

NATCONSUMERS - NATural Language Energy for Promoting CONSUMER Sustainable Behaviour

Residential energy consumption represents the 28% of all EU consumption and if commercial buildings are also considered this percentage increases to 40% (36% of EU CO2 emissions). In this context, is clear that the reduction of consumption in the residential sector should play an important role in energy efficiency programmes and policies as is stated in the recent Energy Efficiency Directive 2012/27/EU.

Most energy efficiency measures implemented in Europe involve technological interventions. In contrast, everyday energy consuming behaviours are largely habitual and therefore the potential of energy savings at home with actions focused in consumer behaviour is really promising. In this context the provision of feedback to consumers has resulted in really promising results, achieving savings in the range of 5-20%.

But some limitations exists. The aim of NATCONSUMERS project is to fill the gaps and advanced in this context, being an essential preparatory activity for the future large scale demonstration of feedback methodologies. The key aim of this project is to develop an advanced and integral user-centered framework for the implementation of efficient energy feedback programmes in the domestic area. Our approach relies in the complete characterisation of the EU energy consumer, and the design of specific personalised actions tailored to each consumer pattern detected based on the use of natural language and emotional contents.

NATCONSUMERS will set the scenario to allow strengthening the dialogue between the EU energy system stakeholders in order to define robustness methodologies exploiting to the maximum the potential of energy feedback approaches, filling the existing gaps not still covered by previous pilots and experiments. NATCONSUMERS consortium brings together representatives of all stakeholders and areas involved in the project. A concise dissemination and awareness programme is proposed to reach the target communities and increase the impact of the project.


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 657672.


NATCONSUMERS: Methodology for the generation of personalized energy recommendations using Natural Language.


The project aims to encompass a "hybrid process" modelling framework that reconciliates semantic inference, rule-based inference, meta-modelling management techniques and knowledge management techniques in order to bring SMEs closer to the Cloud by making it attractive for them to incorporate cloud resources and components for their realization of their goals. The proposed framework implements a layered approach for managing the complexity of bridging the semantic distance from business process to workflow configuration of Business Processes in the Cloud.