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About

Mengge Yuan is a rising researcher in healthcare operations and human-machine systems, with a focus on optimizing autonomous and automated technologies for medical environments. Her work centers on three key areas: stochastic scheduling of autonomous mobile robots (AMRs) in hospitals, layout design and retrieval sequencing in automated drug dispensing systems (ADDSs), and order-picking efficiency strategies for pharmacy automation. In her most-cited paper (2023, 4 citations), Yuan develops a stochastic scheduling model for hospital AMRs, accounting for variable travel and service times to minimize daily costs—a critical contribution to real-world healthcare logistics. Her 2024 study on human-machine cooperation (2 citations) addresses the growing demand for ADDSs driven by aging populations, optimizing both layout and drug retrieval to enhance pharmacy workflow. Another 2023 paper (2 citations) introduces a scattered storage and clustered allocation strategy to improve order-picking efficiency in ADDSs. Yuan’s work bridges operations research and practical healthcare challenges, offering scalable solutions that reduce costs and improve service reliability. Her research is particularly notable for integrating stochastic elements and human factors, making her a promising voice in the future of intelligent healthcare systems.