Rubina Polovina

International Laboratory for Endeavour Architecture (ILEnA)
Measuring Ontologies for Value Enhancement (MOVE) Research Community
Toronto, Ontario, Canada
E-mail: Rubina-at-SystemsAffairs.com
Cell: 647 801 8339

Dr. Rubina Polovina is a computer scientist whose research focuses on endeavor and enterprise architecture, as well as the deep semantic foundations of intelligence. She is a co-founder and co-editor of the MOVE (Measuring Ontologies in Value-seeking Environments) research community and its publications. Her work includes the Upper Modeling Framework (UMF), a semantic framework for understanding complex systems and knowledge dynamics, along with recent contributions to AGI research such as When Fields Co-Model, published in the AGI 2025 proceedings.

See also: SysAffairs.org

Rubina Polovina, PhD is a computer scientist whose work spans conceptual modeling, enterprise architecture, ontology‑based systems, and the deep semantic foundations of Artificial General Intelligence (AGI). Her research explores how meaning, structure, and agency emerge within intelligent systems; both human and machine, through the lens of upper ontologies and knowledge dynamics. She is advancing the Upper Modeling Framework (UMF), a multi‑layered semantic architecture designed to uncover foundational building blocks of intelligence and cognition.

Polovina is the co‑founder and co‑leader of the international MOVE (Measuring Ontologies in Value‑seeking Environments) research community, which brings together scholars and practitioners exploring knowledge-intensive systems, ontology engineering, and socio‑technical adaptation. She also served as co‑editor of the Springer CCIS volume Measuring Ontologies for Value Enhancement (MOVE 2020), which curates cutting‑edge work on enterprise ontologies, complexity, and innovation.

Her scholarly contributions include foundational work on Object‑Oriented (OO) modeling and formal specification, as well as recent publications on complex systems, endeavor architecture, and semantic modeling in times of societal disruption. Her recent research advances the frontier of AGI, including “When Fields Co‑Model: Emergent Meaning and Proto‑Consciousness in Large Language Models via the Upper Modeling Framework” (AGI 2025), which proposes a deep semantic mechanism by which large language models may exhibit proto‑conceptual behaviors.

Polovina is also the lead author of Architecting Intelligence through the Upper Modeling Framework, which articulates a comprehensive approach to deep semantic modeling and its implications for multi‑domain intelligent systems. Her work on modeling complex systems, such as On Understanding and Modelling Complex Systems, Through a Pandemic, has informed dialogue on resilience, societal adaptation, and the role of knowledge flows in dynamic environments.

In addition to her academic research, Rubina Polovina is a leader within the Ontario Public Service, where she founded and continues to lead the Share Your Science annual scientific conference (est. 2019), now one of the largest internal applied‑science events within the provincial government. She also co‑chairs the OPS Science Working Group, fostering cross‑ministry scientific collaboration, prototyping, and adoption of emerging technologies.

Rubina Polovina’s work is characterized by an integrative vision: unifying formal modeling, semantic depth, human creativity, and system-level intelligence to advance both theoretical understanding and real‑world impact. She continues to work at the intersection of deep semantic modeling, AGI architectures, and high‑complexity socio‑technical systems.

Briefly, I have worked in the industry for more than 20 years. Since 2020, I have revived my research, and together with several colleagues, I am developing a framework that supports the modeling and understanding of Artificial General Intelligence (AGI). We would be delighted to share and discuss our findings with you and the members of your forum.