Yuta Seo
Papers
1
Total Citations
162
H-Index
1
About
Yuta Seo is a leading researcher in the intersection of machine learning and materials science, with a primary focus on automating the discovery of two-dimensional (2D) materials. Seo’s most impactful contribution is the development of a deep-learning-based image segmentation algorithm integrated with optical microscopy, which enables the autonomous robotic search for 2D materials. This pioneering work, published in 2020 and cited over 160 times, replaces labor-intensive manual inspection with precise, high-dimensional image recognition, dramatically accelerating the identification of atomically thin crystals. By bridging computer vision and experimental nanoscience, Seo has laid the groundwork for fully automated materials discovery platforms. Their research addresses a critical bottleneck in 2D materials research—the time-consuming process of finding exfoliated flakes—and has inspired a new wave of AI-driven laboratory automation. Seo’s work is notable for its practical impact, directly enabling high-throughput characterization and synthesis of novel van der Waals heterostructures. For students and researchers, Seo exemplifies how deep learning can transform traditional experimental workflows, making materials discovery faster, more reproducible, and scalable.
Research Focus
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Top Papers
- 1