Thomas
Le Bras

Applied behavioral research and AI systems for high-traffic digital products.

• Led applied research from experimental protocol to actionable insight delivery.
• Built behavioral scoring systems operating at the scale of millions of users.
• Translated complex findings into product, UX and commercial decisions with product and leadership teams.

PhD research on personality, visual exploration and user interactions.

• Led large-scale quantitative research on attention and decision-making using eye- and mouse-tracking data.
• Contributed to EmotionsAI, a real-time behavioral segmentation solution based on emotional needs and mouse-movement analysis.
• Developed behavioral metrics for applied Machine Learning systems and published in Scientific Reports, Nature Portfolio in 2024.

Early work across user research, cognitive psychology and Deep Learning.

• Quantitative UX studies and data analysis applied to interfaces and digital campaigns.
• Eye-tracking and cognitive-psychology methods used to study visual attention.
• Convolutional neural networks for image classification in computational neuroscience.