Personality and Consumer Responses to Humorous Advertising

Alina Sterlecchini

This doctoral research examines the relationship between personality and consumer responses to humorous advertising, with a particular focus on between-person differences and within-person variability. The project combines a systematic review of existing evidence with a repeated-measures diary study investigating associations between personality traits, momentary states, and responses to humorous advertising. By integrating between-person and within-person perspectives, the research aims to provide a deeper and more nuanced understanding of variability in consumer responses to humorous advertising.

Genetic Algorithms Applied in Psychometrics

Filoteia Beșleagă

This doctoral research examines the potential of genetic algorithms to advance psychometric measurement and the development of psychological assessment instruments. Drawing on the principles of evolutionary computation and psychometric theory, the project explores how these computational approaches can address complex measurement challenges while accounting for multiple psychometric requirements. By investigating both the capabilities and limitations of genetic algorithms in this context, the research seeks to contribute to the development of more flexible, efficient, and methodologically rigorous approaches to psychological assessment.

Automated Item Generation with Large Language Models

Alexandra Constantinescu

The aim of this doctoral research is to investigate the utility of large language model-based automated item generation as a cost-effective method of item development in psychological and educational testing. Based on the link between language and individual differences in measurement, this project explores the psychometric qualities of generated items and the potential of using item embeddings for a priori item calibration without the need for human data.

Personality Dynamics in The Workplace

Andrei Ion

The aim of this stream of research will be focused on investigating within-person processes in behavior manifestation, with the aim to contribute and provide evidence for more recent theories of personality, such as Whole-Trait Theory and PersDyn, as well as it is intended to have contributions in applied psychology and personnel selection studies, with the development of an instrument that can potentially capture within-person variability at one moment in time.

Context Matters: Personality & Work Outcomes

Raluca Duțu

This stream of research investigates the relationship between personality traits and an extended conceptualization of performance, with a particular emphasis on context and its role.

The current project has two major components. One part investigates boundary conditions of the relationship between personality and work outcomes. The second part offers a distinct perspective: it is a proximal application of this theme in assessment, tackling topics such as contextualization and the frame of reference effect.

Natural Language Processing Applied to Occupational Assessment: Individual Differences and Job Outcomes

Adi-Marian Apostu

The project examines whether psychological constructs relevant for occupational assessment, such as burnout and vocational interests, can be measured from short open-ended texts written in Romanian. It uses transformer-based language models and machine learning, and evaluates the resulting scores for accuracy, discriminant validity, and fairness, as a complement to standardized psychological instruments.

The thesis comprises three studies. The first distinguishes burnout from depression, anxiety, and perceived stress based on self-reported text. The second predicts RIASEC vocational interests from open-ended responses, and the third tests zero-shot, item-level scoring of psychological inventories from free text. The findings aim to support more accessible and evidence-based assessment practices in recruitment, career counseling, employee development, and workplace mental health.