Piotr Krzywicki
Papers
1
Total Citations
2
H-Index
1
About
Piotr Krzywicki is a roboticist whose work centers on the intersection of machine learning and robotic manipulation, with a particular focus on semi-supervised learning to overcome data scarcity in real-world systems. His most-cited paper, "Grasping Student: semi-supervised learning for robotic manipulation" (2023), addresses a critical bottleneck in robotics: the high cost of gathering real-world training data. By designing a system that leverages a small sample of robot experience alongside readily available product images, Krzywicki demonstrates how to scale grasping capabilities without exhaustive physical trials. This approach not only reduces the time and expense of robot training but also opens the door to more adaptable industrial and service robots. While his citation count is still growing—reflecting the early stage of his career—his work has already been recognized for its practical impact on efficient robot learning. Krzywicki’s contributions are particularly relevant for students and researchers interested in bridging the gap between simulation and reality, making robotic manipulation more accessible and data-efficient.
Research Focus
Key Achievements
Top Papers
- 1Grasping Student: semi-supervised learning for robotic manipulation2 citations · 2023