Dr Igor Menezes
| Biography | Dr Igor Menezes is dedicated to the study and application of artificial intelligence, psychometrics, cognitive science and organisational psychology to help organisations better understand and improve how people work. His focus is on transforming research into practical solutions that create measurable benefits for both employees and employers. Whether in academia or industry, he is driven by a commitment to innovation that delivers real-world impact. He is an AI Psychometrician, RSS Chartered Statistician (CStat), Advanced Data Science Professional (AdvDSP), Chartered Psychologist (CPsychol), Associate Fellow (AFBPsS) of the British Psychological Society and Senior Lecturer (Associate Professor) in People Analytics at Hull University Business School. Dr Menezes completed his postdoctoral studies at the University of Cambridge and subsequently worked as a Research Associate at the Judge Business School. With over two decades of academic experience, he has taught undergraduate and postgraduate modules in quantitative methods, psychometrics, research methods, organisational behaviour and people analytics. He has also coordinated research teams and laboratories for more than fifteen years as principal investigator on various grants and funded projects. In addition, he has supervised numerous Master’s and PhD students and published research on the development, adaptation and validation of instruments across fields such as psychology, organisational behaviour, healthcare, education and personality. His research interests span artificial intelligence, computer vision, data science, causal inference, people analytics, psychometrics, statistical programming (R and Python) and advanced quantitative methods in organisational psychology and OB/HRM. He is particularly passionate about integrating AI and computer vision algorithms with psychometric methods to develop innovative, data-driven solutions for individuals and organisations. Committed to bridging the gap between academic research and industry application, Dr Menezes has collaborated with organisations in the UK and Latin America on projects that assess workplace behaviours and identify key indicators for enhancing both individual and organisational performance. He is currently accepting PhD students who are passionate about advancing and applying artificial intelligence, latent trait models, network analysis and causal inference to address complex organisational challenges. His supervisory areas include HR metrics, social cognition and organisational behaviour, offering candidates a unique opportunity to work at the intersection of emerging technologies and real-world business problems. |
|---|---|
| Research Interests | His 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. |
| Teaching and Learning | - Psychometrics - Quantitative methods - Research methods - People Analytics - Predictive modelling (AI) |
| Scopus Author ID | 57208579581 |
| PhD Supervision Availability | Yes |
| PhD Topics | Organisational climate Organisational commitment / engagement Organisational citizenship behaviours Turnover intentions / reasons |