About Us

 

Professor Mark S. Fox

Mark S. Fox is the Distinguished Professor of Urban Systems Engineering at the University of Toronto. He is a Professor of Industrial Engineering and Computer Science, Director of the Urban Data Centre in the University of Toronto’s School of Cities, founding director of the Centre for Social Services Engineering, and head of the Enterprise Integration Laboratory. He is a Fellow of the Association for the Advancement of Artificial Intelligence and the Institute for Electrical and Electronic Engineering. He is the editor of the ISO/IEC 5087 series of city data model standards, an author of the Common Impact Data Standard.

 
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Dr. Megan Katsumi

Megan Katsumi received her PhD from the University of Toronto, where her research at the Semantic Technologies Laboratory focused on foundations for ontology development. Megan completed a postdoctoral fellowship with the University of Toronto Transportation Research Institute (UTTRI) where she contributed to the development of a suite of ontologies for transportation planning to support the iCity-ORF project. Her current research activities are focused on the use of ontologies in asset management and the development of ontology-based standards.

Dr. Bart Gajderowicz

Bart Gajderowicz completed his PhD at the University of Toronto, where he was the Social Service Simulation project director at the Centre for Social Services Engineering research group. His work focused on developing the Ontology for Social Service Needs (OSSN), and the simulation of service usage and client needs in the "Housing First" intervention program. His current work focuses on the development and adoption of the Common Impact Data Standard (CIDS) for measuring the impact of smart city services. This work incorporates the development of service-focused ontologies, data standards, AI language models, and knowledge extraction methods. With a focus on data-driven methods, Bart has applied his work in the areas of social service provisioning and impact measurement, cognitive models for simulating social behaviour, information diffusion in social networks, and identification of social factors in art market trends.