Byungjoo Choi

Papers

Total Citations

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About

Byungjoo Choi is a rising force in construction robotics, with a research focus that bridges human-robot collaboration and AI-driven automation for heavy equipment. His work addresses critical bottlenecks in the digital transformation of construction, particularly the scarcity of domain-specific training data for excavators. In his highly cited 2024 paper on human-robot team performance, Choi demonstrated how emotional responses—such as operator stress or trust—directly impact the efficiency and safety of human-robot teams on construction sites, a novel contribution to the field of human factors engineering. His 2025 study tackles a foundational problem: the lack of diverse, real-world imagery needed to train AI for digital twinning of excavators. By robotizing a miniature-scale radio-controlled excavator, he created a deployable, low-cost platform for generating construction-specific deep neural network (DNN) data, circumventing the prohibitive costs and safety risks of using full-sized machinery. Though early in his career, Choi’s work has already garnered attention (14 and 5 citations, respectively), signaling strong potential for future impact. His research is paving the way for smarter, safer, and more autonomous construction sites.