Luke Barbier
I’m a robotics and ML engineer with a particular interest in JEPA-style world models for physical interaction. I’m interested in building systems that learn predictive latent representations and use them for hierarchical planning, adaptive computation, flexible goal specification, and robust decision-making under partial observability and changing camera viewpoints. More broadly, I care about how learned world models can become reliable components of real robotic systems rather than isolated perception models.

Publications
Collaborative human-autonomy semantic sensing through structured POMDP planning
Burks, Luke, Nisar Ahmed, Ian Loefgren, Barbier, Luke, Jeremy Muesing, Jamison McGinley, and Sousheel Vunnam
Robotics and Autonomous Systems 2021