Papers
4
Total Citations
33
H-Index
2
About
Yikai Zang is a researcher advancing the frontiers of precision manufacturing, with a primary focus on robotic polishing of advanced optical materials. His work centers on developing intelligent, data-driven methods to optimize material removal processes, particularly for challenging substrates like single-crystal silicon and M-ZnS. Zang’s major contributions include pioneering the integration of deep learning with Bayesian-optimized differential evolution algorithms to dramatically improve material removal rate and process efficiency—a breakthrough that has garnered 25 citations for his 2024 paper alone. He has also developed and validated a refined removal function model for M-ZnS using finite element analysis, achieving a relative deviation of less than 8% between simulation and experimental data, enabling high-precision, low-cost batch manufacturing of optical components. Additionally, his investigation into strain rate effects on material removal and surface formation in single-crystal silicon provides fundamental insights for robotic polishing. With a growing citation impact and a portfolio of work that bridges computational modeling, optimization, and practical manufacturing, Yikai Zang is establishing himself as a key innovator in intelligent robotic polishing and optical fabrication.
Research Focus
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