Dr. Elfeki designs and validates structured measurement frameworks for applied AI contexts.

Yasmine Elfeki, Ph.D., is an industrial-organizational psychologist whose work sits at the intersection of psychometrics, artificial intelligence, and data science. She specializes in translating complex psychological constructs into rigorously validated measurement systems that power predictive analytics while preserving theoretical integrity. Dr. Elfeki designs and validates structured measurement frameworks for applied AI contexts. Her work includes scale development, construct operationalization, behavioral indicator mapping, and reliability and validity testing, including internal consistency, inter-rater agreement, and construct validation. She develops behaviorally anchored instruments and evaluation rubrics that transform abstract constructs into measurable variables suitable for predictive modeling. Alongside this measurement work, she builds predictive models and leverages organizational data to generate actionable insights and clear data-driven narratives. Her research interests focus on how individuals interpret social signals in high-stakes environments. She examines how leader cues, identity signals, and contextual framing shape judgments of leadership and competence. In this line of work, she integrates computational methods, including natural language processing and text analytics, to analyze open-ended responses and uncover latent patterns in perception and decision-making. In AI-driven jury simulation contexts, Dr. Elfeki contributes to the empirical evaluation and refinement of simulated juror personas, applying psychometric and computational techniques to assess consistency, construct alignment, and behavioral coherence. Her work advances the development of AI systems that model human judgment in ways that are theoretically grounded and empirically validated.