Samuele Papa
Papers
1
Total Citations
2
H-Index
1
About
Samuele Papa is a rising researcher at the intersection of robotics, artificial intelligence, and cognitive science, with a focus on enabling machines to learn and act through imagination. His work centers on world models—internal representations that allow an agent to simulate the consequences of its actions before executing them in the real world. In his highly cited 2024 paper, "Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination," Papa introduces a novel framework that bridges the gap between abstract simulation and physical reality. By composing modular world models, his approach allows robots to "dream" of possible manipulation sequences, dramatically improving their ability to imitate human demonstrations with realistic, adaptive behavior. This work, already garnering 2 citations in its first year, addresses a critical bottleneck in imitation learning: the failure of current models to directly mirror the actual environment. Papa’s contributions are foundational for the next generation of autonomous robots that can learn from few examples, generalize across tasks, and operate safely in unstructured settings. His research promises to reshape how machines understand and interact with the physical world.
Research Focus
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Top Papers
- 1