Young Jae Shin

Harvard University

Papers

1

Total Citations

15

H-Index

1

About

Young Jae Shin is a pioneering researcher at the intersection of condensed matter physics and artificial intelligence, whose work has significantly advanced the automated fabrication of van der Waals (vdW) heterostructures. His key research areas include machine vision for 2D materials, robotic exfoliation, and the optical characterization of atomically thin layers. Shin’s most notable contribution is the development of a deep neural network-based system for fast and accurate robotic detection of exfoliated graphene and hexagonal boron nitride, a breakthrough that streamlines the construction of quantum material platforms. This work, published in 2020 with 15 citations, demonstrates his ability to merge AI with experimental physics, enabling emergent physical phenomena and novel device applications. By automating the identification of atomically thin layers, Shin has addressed a critical bottleneck in vdW heterostructure research, paving the way for scalable, high-throughput material assembly. His achievements highlight a visionary approach to integrating machine learning into nanomaterial science, making him a key figure in the next generation of quantum device fabrication.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Fast and accurate robotic optical detection of exfoliated graphene and hexagonal boron nitride by deep neural networks
15 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Harvard University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago