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  • Format: ePub

This book is the result of a collaborative and transdisciplinary effort towards a first definition of "dance data", with its complexities and contradictions, in a time where cognitive science is growing in parallel to the need of a renewed awareness of the body's agency in our manyfold interactions with the world.

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Produktbeschreibung
This book is the result of a collaborative and transdisciplinary effort towards a first definition of "dance data", with its complexities and contradictions, in a time where cognitive science is growing in parallel to the need of a renewed awareness of the body's agency in our manyfold interactions with the world.


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Autorenporträt
Carla Fernandes is Principal Investigator, Head of ICNOVA's Research Group on Performance & Cognition, and Professor at FCSH - Universidade Nova de Lisboa, where she directs the ERC-funded "BlackBox LAB Arts&Cognition." Her current research focus is in the intersection of Performing Arts and Cognitive Science, Multimodal Communication, Intangible Cultural Heritage, and New Media. She is fascinated by the complexity of the human mind and non-verbal behavior in creativity settings. She holds a PhD in Linguistics, supervises numerous PhD and MA theses, and is author in international indexed peer-reviewed journals and books. Vito Evola is currently a Researcher in Cognitive Linguistics and Multimodal Communication at the Universidade Nova de Lisboa, having previously lectured and conducted research at universities in Palermo, Berkeley, Cleveland, Aachen, and Geneva. His research lies at the intersection of language, culture, and cognition, and analyses data from both common and more specialized contexts, such as patient-doctor interactions, psychotherapy and forensic interviews, religious discourse, and the performing arts. Cláudia Ribeiro is a Postdoctoral Researcher at FCUL, in the research group LASIGE. She obtained her PhD in Information Systems and Computer Engineering at the University of Lisbon. Her research interests include machine learning, deep learning (focusing on emotion recognition in multimedia content), and interactive systems.