Bribery Tendency Detection

A multidisciplinary study combining behavioural assessments, brain imaging, and eye tracking to understand and predict bribery tendencies among Malaysians from a neuroscience cognitive perspective.

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2- 19 December Meeting
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WhatsApp Image 2026-09-30 at 7.18.44 PM
WhatsApp Image 2026-09-30 at 7.18.44 PM (1)
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2- 19 December Meeting
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This multidisciplinary research project, funded by Universiti Sains Malaysia, investigates bribery practices in Malaysia from a neuroscience cognitive perspective. The study examines how enforcement officers/government agency officers and laypersons think about and respond to corruption by combining behavioural assessments, brain imaging, and eye tracking technology.         

 

Through surveys and interviews, the project first maps the psychological traits and attitudes that may support corrupt behaviour. It then goes deeper,using EEG and eye tracking to observe how the brain and body involuntarily react when individuals are confronted with bribery-related scenarios. The ultimate goal is to combine these multiple data streams using deep learning to develop a predictive model capable of identifying bribery tendencies, contributing to both the scientific understanding of corruption and practical tools for prevention and intervention.

The Team

Meet the researchers behind each part of the project.

Subproject 01

Behavioural and Psychological Profiling of Bribery Practices

Dr. Geshina Ayu Mat Saat

Principal Investigator

Nurul Athirah
Nordin

 GRA

Subproject 02

Neuroimaging and Eye-tracking of Bribery-Related Cognitive Responses

Dr. Mohamed Faiz Mohamed Mustafar

Principal Investigator

Dr. Mohd Faizal Mohd Zulkifly

Psychologist & EEG expert

 

Dr. Aini Ismafairus Abd. Hamid

Cognitive Neuroscientist

 

Siti Mariam

 GRA

 

Subproject 03

Multimodal Bribery Tendency Detection with Machine Learning on EEG, Eye Gaze and Behavioural Features

Dr. Syaheerah Lebai Lutfi

Principal Investigator

 

Samira Ayman Elsamad

GRA

 

Aisyahtul Mardhiah

PhD Candidate