Jeonghyeon Park

Pukyong National University, Sun Moon University

Papers

Total Citations

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About

Jeonghyeon Park is a researcher whose work bridges atmospheric science and advanced manufacturing, with a particular focus on machine learning applications and semiconductor automation. In his most prominent contribution, "A First Approach to Aerosol Classification Using Space-Borne Measurement Data," Park developed a novel machine learning algorithm that classifies aerosol types from satellite data, using AERONET-based datasets as training targets for a random forest model. This work, which has garnered 26 citations, represents a significant step toward automated, remote environmental monitoring. Park’s earlier research in semiconductor manufacturing, exemplified by his study on cluster tool module communication using high-level fieldbuses, demonstrates his versatility. That work, with 8 citations, addressed the critical challenge of integrating distributed module controllers in wafer processing systems through inter-module communication networks. Together, these contributions showcase Park’s ability to apply computational methods to diverse technical domains—from Earth observation to industrial automation—making his research valuable for both environmental scientists and engineers seeking data-driven solutions to complex classification and integration problems.