Carl Falk is an associate professor of quantitative psychology at McGill University with a decade of experience developing and implementing advanced latent variable models across behavioral and health sciences. He combines deep methodological expertise in item response theory, structural equation and multilevel modeling with practical skills in Bayesian statistics, categorical data analysis, and network modeling. A former computer/web programmer, he writes custom implementations in R, Python, Java, C/C++ and Stan and co-authors multiple R packages, often pairing theoretical innovation with large-scale simulation studies. His research spans theory-to-practice: detecting item misfit and aberrant or bot-driven responses in surveys, handling messy real-world data, and designing model selection tools that help substantive researchers make defensible inferences. Based in Montreal, he is known for translating complex quantitative methods into accessible tutorials and collaborative applied work that directly improves measurement and causal inference in applied domains.
10 years of coding experience
14 years of employment as a software developer
BS with comprehensive honors, Double major: Psychology & SE Asian Studies, BS with comprehensive honors, Double major: Psychology & SE Asian Studies at University of Wisconsin-Madison
PhD, Social/Personality Psychology; Minor: Quantitative Methods, PhD, Social/Personality Psychology; Minor: Quantitative Methods at The University of British Columbia / UBC
Contributions:33 commits, 2 PRs, 13 pushes in 1 year 4 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.