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Universities, R&D Groups and Academic Networks

ICAART 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:

Carnegie Mellon University (CMU)

Carnegie Mellon University (CMU) is a global research university with more than 13,200 students, 100,000 alumni and 5,000 faculty and staff. 

CMU has been a birthplace of innovation since its founding in 1900.

Today, Carnegie Mellon University is a global leader bringing groundbreaking ideas to market and creating successful startup businesses.

Award-winning faculty members are renowned for working closely with students to solve major scientific, technological and societal challenges. Carnegie Mellon University put a strong emphasis on creating things—from art to robots. Students are recruited by some of the world’s most innovative companies.

Carnegie Mellon University have campuses in Pittsburgh, Qatar and Silicon Valley, and degree-granting programs around the world, including Africa, Asia, Australia, Europe and Latin America.

The Institute of Cognitive Sciences and Technologies (ISTC-CNR)

The Institute is involved in research, enhancement, transfer and training activities on intelligent systems, either natural or artificial, human or non-human, individual, interactional or social. In particular: - their architectures, structures and processes; - their relationship with the (internal and external) environment; - their evolution, cognitive development and learning. The approach is strongly interdisciplinary and multi-methodological: theoretical, formal, computational, simulative, robotic and experimental. ISTC is committed to advancing the field of Cognitive Sciences through research in several areas: Cognitive, communicative and linguistic processes: acquisition, elaboration, deficit, multimodality, communication technologies. Theory, analysis and technology of spoken language and of linguistic variability. Cognitive development, learning and socialization in children and non-human primates. Artificial intelligence, artificial life, artificial societies. Cognitive technologies, neural networks, autonomous robotics. Social cognition: behaviour, motivations, cultural transmission and cultural processes. Decision-making and cooperation technologies. Environmental quality, health and society: prevention, education, integration, handicap, technological planning. In practice, we apply a range of tools and methodologies for understanding the mechanisms and processes that underlie cognition at different levels.

MixedEmotions. Social Semantic Emotion Analysis for Innovative Multilingual Big Data Analytics Markets

MixedEmotions will develop innovative multilingual multi-modal Big Data analytics applications that will analyze a more complete emotional profile of user behavior using data from mixed input channels: multilingual text data sources, A/V signal input (multilingual speech, audio, video), social media (social network, comments), and structured data. Commercial applications (implemented as pilot projects) will be in Social TV, Brand Reputation Management and Call Centre Operations. Making sense of accumulated user interaction from different data sources, modalities and languages is challenging and has not yet been explored in fullness in an industrial context. Commercial solutions exist but do not address the multilingual aspect in a robust and large-scale setting and do not scale up to huge data volumes that need to be processed, or the integration of emotion analysis observations across data sources and/or modalities on a meaningful level. MixedEmotions will implement an integrated Big Linked Data platform for emotion analysis across heterogeneous data sources, different languages and modalities, building on existing state of the art tools, services and approaches that will enable the tracking of emotional aspects of user interaction and feedback on an entity level. The MixedEmotions platform will provide an integrated solution for: large-scale emotion analysis and fusion on heterogeneous, multilingual, text, speech, video and social media data streams, leveraging open access and proprietary data sources, and exploiting social context by leveraging social network graphs; semantic-level emotion information aggregation and integration through robust extraction of social semantic knowledge graphs for emotion analysis along multidimensional clusters.


Inside-Dem is a project funded by the German Federal Ministry of Education and Research. The goal of the project is to develop a technical situation-based decision support system for coping with challenging behaviour exhibited by people with dementia in home settings. To achieve that, the "Mobile Multimedia Information Systems group" (MMIS) at the University of Rostock investigates methods for (1) recognising challenging behaviour of people with dementia based on sensors and behaviour assessment models and for (2) selecting an appropriate intervention strategy based on the recognised agitated behaviour. MMIS works in the area of Ambient Intelligence, focusing on the topics of intention and activity recognition. One of the chair’s innovative contributions is the CCBM Tool (Computational Causal Behaviour Modelling), which provides a language for defining computational models of user behaviour together with software for the automatic translation of these models into Bayesian filters. Among other, CCBM has been used for recognising the behaviour of groups in intelligent environments, the actions and context in kitchen scenarios, as well as for the activity pattern analysis for elder care nurses and maintenance personnel.