Dr Igor Menezes
| Biography | Igor Menezes is a psychometrician, RSS Graduate Statistician (GradStat), Chartered Psychologist (CPsychol) and Associate Fellow (AFBPsS) of the British Psychological Society, and Senior Lecturer (Associate Professor) in People Analytics at Hull University Business School. He carried out his first postdoctoral studies at the University of Cambridge, from 2013 to 2014, working on the implementation of multidimensional item response theory into the Concerto platform. In 2016, he was appointed as a research associate in the Judge Business School, University of Cambridge to work on a project in partnership with BOSTES/NESA, Australia. He has worked as an academic for over two decades, delivering modules on quantitative methods, psychometrics, research methods, organisational behaviour and people analytics to undergraduate and postgraduate students. Research-wise, he specialises in building high-level psychometric and statistical models to tackle various human-centric challenges across different domains. His work involves harnessing psychological constructs to address real-world issues, empowering organisations and individuals to make informed decisions and drive positive outcomes. He has more than seventeen years of experience coordinating teams and laboratories as a researcher and principal investigator for several research grants and funded projects. He has supervised Master’s and PhD students and published papers regarding the development, adaptation and validation of instruments applied to different fields, such as psychology, organisational behaviour, healthcare, education, personality and accounting. His research interests cut across different fields such as artificial intelligence, computer vision, data science, causal inference, people analytics, psychometrics and statistical programming (R and Python), as well as the application of advanced quantitative methods in Organisational Psychology and OB/HRM. While passionate about exploring a wide array of research topics, he is primarily driven by the prospect of blending AI and computer vision algorithms with psychometric techniques to enhance solutions for individuals and businesses. By aiming to bridge the gap between academia and industry when it comes to fostering innovation, he has developed projects with companies in the UK and Latin America aimed at the assessment of behaviours in the workplace and indicators that can ultimately improve individual and organisational performance. He is accepting PhD students interested in an evidence-based approach to the study of people analytics and in the development and application of psychometric models and AI to the investigation of micro- (e.g., organisational commitment, organisational climate, organisational engagement, turnover intentions, wellbeing etc) and meso-organisational behaviours (e.g., agile team dynamics). |
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| Research Interests | My main research interests revolve around designing Complex Networks to investigate psychological constructs and understand human behaviours within the following areas: - AI, computer vision, interpretable, and explainable machine learning: Leveraging complex network design to understand patterns and relationships in AI and computer vision applications when investigating psychological constructs. - Psychometrics: Employing complex network designs to develop and validate psychometric instruments, mapping intricate relationships between psychological constructs and behaviours using psychometric networks. - People Analytics: Applying complex network structures, such as Bayesian networks and psychometric networks to analyse people data. - Causal Inference: Designing causal graphs to infer causal relationships between variables, enabling a deeper understanding of causal mechanisms underlying human behaviours. Topics: - Micro-organisational behaviours (e.g., organisational commitment, organisational citizenship behaviours, employee turnover, etc.): Investigating behaviours using complex network analysis to uncover underlying patterns and dynamics within organisational contexts. - Meso-organisational behaviours: Analysing behaviours such as team dynamics through the lens of complex networks to identify key factors influencing team performance and collaboration. - Macro-organisational behaviours: Exploring behaviours like organisational climate and culture by employing complex network approaches to capture the multifaceted relationships and influences within organisational structures. - Individual differences: Exploring individual differences in personality and personal values using complex network models, shedding light on the interconnections between traits and behaviours. |
| Scopus Author ID | 57208579581 |