Diar Abdlkarim

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About

Diar Abdlkarim is a researcher at the intersection of human-robot interaction and robotic manipulation, with a focus on making robot behavior more intuitive and socially aware. Their work addresses a critical gap in robotics: while humans naturally adapt their grasp and movements during handovers to accommodate a partner’s capabilities, current robots lack this understanding. Abdlkarim’s most-cited paper, "Robot, Pass Me the Tool: Handle Visibility Facilitates Task-oriented Handovers" (2022, 12 citations), demonstrates how handle visibility and human-like adaptation can significantly improve the success of human-robot object transfers. This work highlights the importance of designing robots that perceive and respond to human cues, moving beyond rigid, pre-programmed interactions. Additionally, Abdlkarim contributed to "PrendoSim: Proxy-Hand-Based Robot Grasp Generator" (2021, 2 citations), an open-source simulation tool that generates realistic robot grasps to support sim-to-real transfer learning. By leveraging NVIDIA’s physics engine, PrendoSim helps bridge the gap between simulated training and real-world robot performance. Abdlkarim’s research is paving the way for more seamless, cooperative human-robot collaboration, with potential applications in manufacturing, healthcare, and assistive robotics.