Papers

3

Total Citations

39

H-Index

3

About

Jae Gyeong Choi is a leading researcher at the intersection of advanced manufacturing and artificial intelligence, with a primary focus on robotic machining of carbon fiber-reinforced plastics (CFRP). His work addresses critical challenges in aerospace and automotive manufacturing, particularly the pervasive issue of delamination during drilling processes. Choi’s most impactful contribution is his development of a multimodal 1D Convolutional Neural Network (CNN) for real-time delamination prediction in robotic CFRP drilling—a paper that has garnered 31 citations since 2024, reflecting its immediate relevance to industry and academia. He has further advanced the field by pioneering an AI-augmented digital twin framework that enhances machinability in robotic CFRP processes, and by creating an innovative method for accurate sensor-to-machined-surface image generation, enabling operators to promptly identify delamination that compromises long-term material durability. His work uniquely bridges deep learning, sensor fusion, and digital twin technologies to transform how manufacturers monitor and control composite machining quality. Choi’s research is particularly notable for its practical industrial applications, offering real-time solutions to one of the most persistent problems in composite manufacturing—ensuring the structural integrity of critical components.

Research Focus

Key Achievements

3
H-Index
3
Papers
39
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal 1D CNN for delamination prediction in CFRP drilling process with industrial robots
31 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Ulsan National Institute of Science and Technology, University of Maryland, College Park

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago