AI-Driven Analysis of Human Social Behavior
ML and motion capture to model physical/physiological behaviors; predictive analytics, next-gen human-machine interfaces.
Research Impact
Advanced machine learning for social behavior analysis
Project Details
Scalab/CRISTAL Lab
Research – Machine Learning Social Behavior
2017
Mission
Research Scientist ML / AI / Predictive Modeling
Machine Learning Social Behavior
12 months / Lille, France
Predictive modeling: creation of ML models for analysis of human physical and physiological behaviors (notably via CNN 1D and RNN). Motion capture data processing: extraction and transformation of signals for behavioral analysis. Riemannian projections: application of advanced geometric techniques to represent movement dynamics.
Contexte & Environnement
SCALAB/CRISTAL LAB faced the complex challenge of understanding and modeling human social behavior through advanced machine learning techniques. The interdisciplinary nature of the project required bridging behavioral sciences, AI, and social neuroscience to create predictive models for human movement patterns and physiological responses.
Interdisciplinary collaboration with data scientists, psychologists, and physiologists
Python, R, MATLAB with TensorFlow/Keras, Motion Capture Systems, OpenPose
Objectifs Cles
Technologies & Infrastructure
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