Haoping Xu
Papers
10
Total Citations
337
H-Index
6
About
Haoping Xu is pioneering the integration of artificial intelligence and robotics to transform chemistry laboratories into autonomous, intelligent workspaces. Their research centers on three key areas: large language models for robotic chemistry automation, computer vision for lab material recognition, and multi-view perception of transparent objects. Xu’s most impactful contribution is the development of ORGANA, a robotic assistant that automates chemistry experimentation and characterization—a system that has garnered over 110 citations across its publications. Their 2023 paper on using large language models to translate natural language instructions into robot-executable plans for chemistry experiments (98 citations) represents a breakthrough in human-robot interaction for scientific discovery. Additionally, Xu created the Vector-LabPics dataset for recognizing materials and vessels in lab settings (67 citations), addressing a critical gap in computer vision for scientific environments. Their work on MVTrans enables robots to perceive transparent objects through multi-view RGB-D inputs, essential for precise manipulation in labs. With over 330 total citations and a growing portfolio of high-impact papers, Haoping Xu is shaping the future of automated scientific experimentation.
Research Focus
Key Achievements
Top Papers
- 1Large language models for chemistry robotics98 citations · 2023
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- 4MVTrans: Multi-View Perception of Transparent Objects29 citations · 2023
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- 6Chemistry Lab Automation via Constrained Task and Motion Planning13 citations · 2022
- 7MVTrans: Multi-View Perception of Transparent Objects6 citations · 2023
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