Can Mekik
Dr. Mekik holds a Ph.D. from the Department of Cognitive Science at Rensselaer Polytechnic Institute, and an M.Cog. from the Department of Cognitive Science at Carleton University. He obtained his Hon. B. Sc. at the University of Toronto, where he studied cognitive science, mathematics, and computer science. Prior to joining U of T in 2023, he was a postdoctoral researcher in the Department of Psychology at Université du Québec à Montréal.
Dr. Mekik's research focuses on developing computational models of psychological processes in cognitive tasks and psychometric tests. He is interested in applying this research to better understand human reasoning and learning, improve the design and interpretation of psychometric tests, and develop new insights regarding human cognitive architecture and cognitive systems.
Education
- PhD, Rensselaer Polytechnic Institute
- MCog, Carleton University
- Hons. BSc, University of Toronto
Research Interests
- Cognitive Modeling
- Cognitive Architecture
- Object Perception
- Relational, Logical, & Analogical Reasoning
- Perception-Cognition Interface
- Motivation & Cognitive Control
Publications
- Mekik, C. S. and Galang, C. M (2022). Cognitive Science in a Nutshell. Cognitive Science, 46(8), e13179.
- Mekik, C. (2021). Logic Programs as Executable Experimental Task Specifications. Proceedings of the Annual Meeting of the Cognitive Science Society, 43.
- Mekik, C.; Sun, R.; and Dai, D. Y. (2018) Similarity-Based Reasoning, Raven’s Matrices, and General Intelligence. In Jérôme Lang (Ed.), Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-2018; 1576–1582).