Sam Creasey
Papers
1
Total Citations
9
H-Index
1
About
Sam Creasey is a rising force in robotics and artificial intelligence, specializing in whole-body manipulation and reinforcement learning. Their seminal work, "Learning contact-rich whole-body manipulation with example-guided reinforcement learning" (2025, 9 citations), pioneers a novel framework that enables robots to master complex, full-body tasks—like manipulating large objects—by integrating diverse human-inspired strategies. This approach bridges the gap between fine motor skills, such as dexterous in-hand manipulation, and gross motor skills requiring extensive contact with multiple body parts. Creasey’s research addresses a critical challenge in robotics: teaching machines to leverage rich physical interactions beyond simple grippers, advancing applications in manufacturing, healthcare, and assistive technologies. Though early in their career, their work has already garnered attention for its innovative use of example-guided learning to accelerate policy training, reducing the need for exhaustive simulation or human demonstration. By focusing on contact-rich dynamics, Creasey is shaping a future where robots can fluidly adapt to unstructured environments, making them more capable collaborators. Their contributions promise to redefine how autonomous systems interact with the physical world, marking them as a researcher to watch in embodied AI.
Research Focus
Key Achievements
Top Papers
- 1