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Two essential facets of human intelligence are:
the ability to learn from experience (in various forms of data) and perform proficiently, or even excel, when faced with similar situations or adapting to new circumstances, and
the ability to maintain an internal (abstract) state of knowledge (typically in the form of structured data) and reason about that knowledge to derive new conclusions.
In AI, these abilities are partially embodied by [Machine Learning] and [Knowledge Representation and Reasoning], respectively.
My research is situated within the realm of AI, with a particular focus on Logics for Knowledge Representation and Reasoning (KR or KRR). KR is concerned with the study of how beliefs, intentions, and value judgments of an intelligent agent can be expressed in a transparent, symbolic notation suitable for automated reasoning. As one of AI's longest-standing areas, it has been widely acknowledged that knowledge and reasoning are integral components of intelligent behavior. Presently, I am working on Description Logics (DLs) and DL-based Ontologies. DLs are logical formalisms—formal languages with well-defined syntax and semantics—used for representing knowledge about a particular domain. With a rich history in AI, DLs are designed to provide a formal, precise description of domain knowledge and facilitate efficient reasoning over that knowledge. Recently, DLs have gained significant momentum as they form the logical basis of several widely-used ontology languages, such as the W3C Web Ontology Language (OWL)
Two essential facets of human intelligence are:
the ability to learn from experience (in various forms of data) and perform proficiently, or even excel, when faced with similar situations or adapting to new circumstances, and
the ability to maintain an internal (abstract) state of knowledge (typically in the form of structured data) and reason about that knowledge to derive new conclusions.
In AI, these abilities are partially embodied by [Machine Learning] and [Knowledge Representation and Reasoning], respectively.
My research is situated within the realm of AI, with a particular focus on Logics for Knowledge Representation and Reasoning (KR or KRR). KR is concerned with the study of how beliefs, intentions, and value judgments of an intelligent agent can be expressed in a transparent, symbolic notation suitable for automated reasoning. As one of AI's longest-standing areas, it has been widely acknowledged that knowledge and reasoning are integral components of intelligent behavior. Presently, I am working on Description Logics (DLs) and DL-based Ontologies. DLs are logical formalisms—formal languages with well-defined syntax and semantics—used for representing knowledge about a particular domain. With a rich history in AI, DLs are designed to provide a formal, precise description of domain knowledge and facilitate efficient reasoning over that knowledge. Recently, DLs have gained significant momentum as they form the logical basis of several widely-used ontology languages, such as the W3C Web Ontology Language (OWL)
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WWW 2024pp.1945-1953, (2024)
PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023pp.3444-3452, (2023)
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