Bart Gajderowicz
Adjunct Assistant Professor @Department Of Mechanical & Industrial Engineering, University Of Toronto
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WORK HISTORY
Adjunct Assistant Professor @Department Of Mechanical & Industrial Engineering, University Of Toronto
I am an Adjunct Assistant Professor (status only) at the Mechanical and Industrial Engineering Department (AI and Information Engineering Group) at the University of Toronto, where I collaborate with Professor Mark Fox in the Urban Data Research Centre.
EDUCATION
University of Toronto
Doctor of Philosophy (PhD), Mechanical and Industrial Engineering
Toronto Metropolitan University
Bachelor’s Degree, Computer Science
Toronto Metropolitan University
MSc, Computer Science
SKILLS
ABOUT BART GAJDEROWICZ
I am the Executive Director and a Research Fellow at the Urban Data Centre, School of Cities, University of Toronto. I am also a Research Fellow at the Centre for Social Services Engineering. I work on artificial intelligence, specifically ontology engineering, natural language understanding (NLU), social simulation, and advanced analytics on knowledge graphs, with applications in Smart Cities.Previously, I was a Postdoctoral Research Fellow in the Industrial Engineering Department at the University of Toronto, and a member of the Centre for Social Services Engineering under the supervision of Professor Mark Fox. I hold a PhD in Industrial Engineering from the University of Toronto, under the supervision of Professors Mark S. Fox and Michael Grüninger. During my PhD, I was the Project Director of the Simulator project at the Centre for Social Services Engineering. I was also a Postdoctoral Research Fellow (Mitacs) in the Computer Science Department at Lakehead University under the supervision of Prof. Vijay Mago, a Senior Research Scientist at Wondeur Ai. I was also a postdoctoral researcher at Tata Consultancy Services (TCS) at the Behavioural Business and Social Sciences, Tata Research Development and Design Centre.The long-term goal of my research is the application of artificial intelligence (AI) techniques towards understanding human behaviour. This research focuses on Human-AI interaction, collaboration, and behaviour analysis where AI- understands human reasoning- perceives humans as bounded rational agents- incorporates data-intensive behaviour modelling- supplements the human decision-making process- predicts human goal-driven behaviour, and- supplements data-poor domains with behaviour theories from psychology, sociology, and economics.
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