Hi, I’m Can (pronounced like ‘John’). I am an Assistant Professor at the Department of Psychology and University College (Cognitive Science) at the University of Toronto.

I am interested in simulating mental processes and using formal systems to better understand how the mind works. The main line of my current work is rooted in developing an integrative understanding of human response processes in psychometric cognitive ability tests and other cognitive tasks. I am interested in using such work to better understand human reasoning processes, improving and refining the design and interpretation of psychometric tests, and developing more versatile and transparent (artificial) cognitive systems. I am the creator and maintainer of pyClarion, an open source Python library for the Clarion cognitive architecture.

Prior to my position at the University of Toronto, I held a postdoctoral position at Université du Québec à Montréal, where I worked with Henry Markovits. I completed my PhD at the Department of Cognitive Science at Rensselaer Polytechnic Institute, where I worked with Ron Sun, and I obtained a Master of Cognitive Science from Carleton University under Jim Davies. I obtained my undergraduate degree from the University of Toronto.

Selected 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).