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Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação (FEEC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Associate Professor and Head of the Department of Computer and Automation Engineering (DCA) at the Faculty of Electrical and Computer Engineering (FEEC) at the State University of Campinas (Unicamp). Electrical Engineer graduated from Unicamp in 2001. Master (2006) in Mobile Communications from Politecnico di Torino (Italy). Master (2009) and PhD (2015) in Computer Engineering from Unicamp. Experience in guiding research projects in generative AI, multimodal AI and Affective Computing. Coordinator of the line of research in Cognitive Architectures at the Artificial Intelligence and Cognitive Architectures Hub (H.IAAC) at Unicamp. Member of the Brazilian Institute of Data Science (BI0S). Enthusiastic about scientific dissemination for children and young people. Deputy Coordinator of the Unicamp Exploratory Science Museum, since August 2018. (Source: Lattes Curriculum)
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Curating and classifying historical collections are essential processes for preserving cultural heritage, but they are often performed manually, leading to slow progress and increased susceptibility to errors. This project addresses the specific challenge of classifying and clustering movable types and ornaments into typographic families, using the collection of the Museu Paulista as a ca…
Studied since the 1950s, cognitive architectures stand out as a promising area in artificial intelligence studies. In particular, the development of cognitive architectures for mobile devices and personal assistants is observed. One of the main challenges within this application lies in the difficulty of evaluating the proposed models due to the scarcity of relevant data for use in resear…
Expressive facial animations are seen by viewers as more natural (little rejection and strangeness to the content) when they are in tune with the content and the way it is communicated by the interlocutor. In this context, several existing methods lose flexibility, as they are dependent on pre-determined emotional labels or facial expression models, which limits a reliable representation …
Research guided by large volumes of data and machine learning has shown great potential in revealing novelties and bringing significant advances in several areas of basic and applied sciences. Organic Chemistry and, more specifically, Organic Synthesis has benefited from this new approach concerning the prediction of organic reactions and retrosynthesis. Several advances are described in …
The increase in the frequency and intensity of extreme weather events is considered one of the evidences and one of the most immediate effects of climate change on our planet. Such changes have a direct impact on human health. The study of the correlation between meteorological parameters and the occurrence of some diseases makes it possible to develop systems of resilience and adaptation…
The "Big Data" era is characterized by the availability of a large amount of data related to a wide variety of phenomena, from human, natural and economical events. In this context, the ability of modeling and understanding the universe around us is closely related to the extraction of knowledge from these datasets. Among the theories and computational tools for extracting data informatio…
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