Davood Tofighi is an Associate Professor of Mathematics & Statistics at the University of New Mexico. His research focusses on developing and evaluating statistical methodologies that enhance the robustness of statistical inferences in various analytical domains. He is particularly interested in causal inference, application, and development of direct acyclic graph (DAG) in causal mediation analysis, statistical and Monte Carlo sensitivity analysis, generalized linear mixed-effects model, multivariate statistics, categorical data analysis, and the judicious application of machine learning techniques to health data.

Dr. Tofighi’s substantive research focuses on amplifying the replicability of statistical methods in the context of educational, health and prevention science. He is also interested in optimizing drug delivery formulations, a critical area of study with far-reaching implications for cancer and COVID-19 research. As an Associate Editor for the Quantitative Psychology and Measurement specialty section of Frontiers in Psychology, Dr. Tofighi plays an active role in the academic community, ensuring the dissemination of rigorous research to a broader audience. Dr. Tofighi acknowledges the support of funding institutions such as NASA, NSF, and NIH, which have been instrumental in enabling his research pursuits. His academic journey reflects his multidisciplinary approach, with a Ph.D. in Quantitative Methods in Psychology from Arizona State University, complemented by an M.A. in Educational Psychology. Additionally, he has earned M.Sc. and B.Sc. degrees in Industrial and Systems Engineering.