Mahsa Ghafarianzadeh
Papers
1
Total Citations
21
H-Index
1
About
Mahsa Ghafarianzadeh is a roboticist whose research lies at the intersection of perception, manipulation, and autonomous learning. Her most influential work introduces a pioneering framework for simultaneous localization, mapping, and manipulation (SLAM+M) that enables a robot to discover, track, and reconstruct unknown objects in its environment without any prior training data. By fusing RGBD sensing with a manipulator’s actions, her system allows a robot to autonomously segment and model novel objects while building a dense 3D map—a critical step toward truly unsupervised robotic learning. This foundational paper has garnered 21 citations and laid the groundwork for subsequent advances in open-world object discovery and interactive perception. Ghafarianzadeh’s contributions are particularly notable for bridging the gap between geometric mapping and semantic understanding, empowering robots to not only see their surroundings but to physically interact with and learn from them. Her work continues to inspire researchers in embodied AI, manipulation, and lifelong robotic learning.
Research Focus
Key Achievements
Top Papers
- 1