Knowledge Graphs
knowledge graphs
Vito Trianni
A fixed-term research position is open for a post-doc, or for a PhD student nearing the end of his doctoral program. The goal of the research is to study hybrid collective intelligence systems for decision support in complex open-ended problems. It involves the design and implementation of a hybrid collective intelligence system to exploit the interaction between human experts and artificial agents based on knowledge graphs and ontologies for knowledge representation, integration and reasoning.
Vito Trianni, Ph.D.
Two two-years Research Assistant positions are available at the Institute of Cognitive Sciences and Technologies, Italian National Research Council, starting as early as February 2023. The selected candidates will have the opportunity to work on the research track of HACID (http://hacid-project.eu/), which is an is an HORIZON Innovation Action, a collaborative project funded under the Horizon Europe Programme, within the topic 'AI, Data and Robotics at work'. HACID develops a novel hybrid collective intelligence for decision support to professionals facing complex open-ended problems, promoting engagement, fairness and trust. The focus of these fellowships is design and development of knowledge graphs and collective intelligence methods in the context of two application domains: medical diagnostics and decision support for climate change adaptation policies.
Spike-based embeddings for multi-relational graph data
A rich data representation that finds wide application in industry and research is the so-called knowledge graph - a graph-based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context-aware predictions in these information-packed environments.