Zhi Ji

Papers

Total Citations

118

H-Index

About

Zhi Ji is a pioneering researcher at the intersection of artificial intelligence, robotics, and autonomous scientific discovery. Their work centers on developing intelligent systems that can understand natural language and execute complex tasks in physical environments, with a particular focus on automating laboratory experiments. Ji's most impactful contribution, "Large language models for chemistry robotics" (2023, 98 citations), introduces a groundbreaking approach that enables robots to translate natural language instructions into executable plans for chemistry experiments, effectively bridging the gap between human communication and robotic action through the integration of large language models with task and motion planning. This work represents a significant leap toward fully autonomous scientific laboratories. In related research, Ji has explored "Errors are Useful Prompts" (2023, 18 citations), developing verifier-assisted iterative prompting techniques that improve the reliability of robot task plans generated from high-level instructions. Earlier in their career, Ji contributed to agricultural technology with work on automated height estimation of biomass sorghum using top-down imaging approaches. Through their innovative fusion of natural language processing and robotics, Ji is helping to shape a future where scientists can interact with autonomous laboratory systems as naturally as they would with human colleagues.