Sooyoung Lee

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Assistant Professor

Chung-Ang University

South Korea

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About

Sooyoung Lee is an Assistant Professor at Chung-Ang University, South Korea. His research areas focus on deep learning applications in non-destructive testing, material characterization, and biological predictions. His recent articles include work on diffusion-enabled defect generation, stress-strain characterization from ultrasonic measurements, and the classification of wafer map failure patterns. Professor Lee's contributions also extend to the monitoring of structural integrity and advancements in photoacoustic imaging techniques.

Recent Grants

Grant: Close

Innovative POSTECHIAN Fellowship

Open Date: 2022-05-01

Close Date: 2023-02-01

Grant: Close

High-Potential Individuals Global Training Program of International Joint Research

Open Date: 2019-07-01

Close Date: 2020-12-01

Articles (10)

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2025

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2025

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2025

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2025

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2023

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2023

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2023

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2023

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2023

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2022

Collaborators (2)

Seo-Yeon Park

The Catholic University of Korea

SOUTH KOREA

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HYUNG JIN LEE

Korea Research Institute of Standards and Science

SOUTH KOREA

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Sooyoung Lee

Research Interests

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About

Recent Grants

Articles (10)

DiffectNet: diffusion-enabled conditional target generation of internal defects in ultrasonic non-destructive testing

Deep learning-enabled accurate and interpretable stress–strain characterization from ultrasonic measurements

Deep learning-accelerated multiple design generation for sound-absorbing metaporous materials

Intelligent metallic loose part monitoring in three-dimensional structures using convolutional neural networks and the position-invariant loss function

A Physics-informed and data-driven deep learning approach for wave propagation and its scattering characteristics

Deep learning predicts the differentiation of kidney organoids derived from human induced pluripotent stem cells

Wafer map failure pattern classification using geometric transformation-invariant convolutional neural network

Deep Learning Enhances Multiparametric Dynamic Volumetric Photoacoustic Computed Tomography In Vivo (DL‐PACT)

Deep learning-based prediction and interpretability of physical phenomena for metaporous materials

Predicting multipotency of human adult stem cells derived from various donors through deep learning

Collaborators (2)

Seo-Yeon Park

HYUNG JIN LEE

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