Dr Paul Barrett

Brief Résumé

ABOUT ME

Paul Barrett received his Ph.D. in personality psychometrics from the University of Exeter, UK. He began work as a research scientist and eventually co-director of the Biosignal Lab at the University of London’s Institute of Psychiatry for 14 years, Chief Scientist at two of the UK’s High Security Forensic Psychiatric hospitals, Chief Psychologist at Mariner7 (Carter Holt Harvey plc, NZ), Chief Research Scientist at Hogan Assessment Systems Inc (US), and adjunct Professor of Psychometrics within the University of Auckland Business School, NZ. He has held the position of Honorary Professor of Psychology at the University of Auckland (NZ) until 2019. Currently he is Chief Research Scientist at Cognadev (UK and SA).

He is an author of several commercial psychological test instruments; developer of the single-item graphical profiler class of psychological assessment technologies, person-target kernel and ‘filter-function’ distance-function algorithms for large-volume candidate selection applications, and an author of over 120 peer-reviewed research articles and book chapters, as well as many technical and strategic whitepapers and blog articles.
He is the section editor of the academic journal Personality and Individual Differences, a consulting editor for the Journal of Personality Assessment, and a member of the editorial boards of the journal Frontiers in Psychology: Quantitative Psychology and Measurement, and the new journal: Personality Science. He is a UK BPS Chartered Psychologist (Associate Fellow) and a member of the American Psychological Association Society for Industrial and Organizational Psychology, and the American Association for the Advancement of Science.

His fields of expertise span measurement theory, actuarial analytics, psychometrics, validity and commercial evidence-base construction and evaluation, the psychology and assessment of individual differences, visual analytics, and non-quantitative computer-intensive data analysis and predictive/evolved-over-time modeling methodologies.

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