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Industrial AI Laboratory

Publication

Journal Publication

In Review/Preparation

  1. MoSE: Mixture-of-Signal-Experts for Versatile Large Language Model-based Signal Processing
  2. Language Model-driven Cross-modal Symbolic Regression for Discovery of Governing Equations
  3. Physically-aligned Flow Matching for Learning Latent Trajectories of Transient Dynamics
  4. Optimizable Path-guided Diffusion Model for Deep Generative Structures
  5. Score-based Combinatorial Diffusion Model for Selective Generative Designs of Metasurfaces
  6. A Novel Approach of Continual Fine-Tuning for Preserving Domain Specialization of Language Models
  7. PINAS: A Novel Approach of Physics-informed Neural Architecture Search
  8. Tri-modal Diffusion Model for Targeted Generative Designs of Scattering Objects
  9. Physics-informed Approach for Posture-Adaptive Intrabody Potential Prediction
  10. Fine-Tuned Large Language Model for MELCOR Automation
  11. Deep Generative and Explainable Prompt-guided Latent Diffusion: A Case Study on 3D Drone Design
  12. DroneMorph: 3D Drone Shape Dataset for Design Optimization
  13. Physics-informed Deep Operator Learning for Vehicle-level Thermal-Stress Surrogate Model
  14. CT-DeepONet: Causality-transferred Physics-informed Deep Operator Network for Multi-layered Heat Spreading Behaviors
  15. Physics-informed Deep Operator Networks for Learning Plasma Drift-diffusion Behaviors
  16. REALM: A Layer-wise Transformer Model for Real-time Defect Monitoring in Additive Manufacturing
  17. Expert-embedded Language Model for Autoheuristic Optimization of Physics-informed Neural Networks, submitted 
  18. Large Language Model-enhanced Multi-agent System for Seamless Design and Manufacturing Processes, submitted 
  19. Uncertainty-aware and Mechanistically-regularized Spiking Neural Networks for On-board Motor Degradation Estimation in Steer-by-wire Systems, submitted 
  20. DANA: Diffusion-based Aerial Noise Auralization for Realistic Synthesis of Quadcopter Noise, submitted 
  21. Dual-Encoder Generative Anomaly Detection for Intelligent Surface Inspection, submitted 
  22. Prompt-guided Diffusion Approach for Deep Generative Vehicle Designs under User-defined Specifications, submitted 
  23. Physics-informed Neural Networks Combined with Gaussian Processes for Multichip Module Layout Optimization, submitted 
  24. Attention-based Adaptive Learning Approach for Intelligent Anti-drone Monitoring System, submitted 
  25. Language Model-driven Anomaly Detection and Interpretation in Chaotic Signals via Temporal-Dynamics-aware Embedding, submitted 
  26. GAPI-DeepONet: Geometry-adaptive Physics-informed DeepONet for Fluid Dynamics, submitted

Published

  1. Donghyun Ra, Jaeryun Lee, Minwoo Lee, Seongmin Kwak, Seungchul Lee, and Sooyoung Lee, "Physics-informed Machine Learning across Manufacturing Processes: Recent Advances, Challenges, and Directions", accepted for the publication in Journal of Manufacturing Systems (IF=14.2, JCR Top 0.5%)
  2. Dongwon Lee, Hyung Jin Lee, Choon-Su Park, and Sooyoung Lee, "DiffectNet: Diffusion-enabled Conditional Target Generation for Non-destructive Ultrasonic Defects", Mechanical Systems and Signal Processing 240 (1), 113454, 2025 (IF=8.9, JCR Top 3.0%) [Link]
  3. Keonhyeok Park, Jun Hyeong Park, Bumsoo Park, Hyung Jin Lee, Sooyoung Lee, Iljoo Jeong, Anna Lee, Choon-Su Park, and Seungchul Lee, "Deep Learning Framework for Image Enhancement of Phased Array Ultrasonic Imaging", Results in Engineering, 106929, 2025 (IF=7.9, JCR Top 3.1%) [Link]
  4. Changhyeon Yoon, Seonghyun Park, and Sooyoung Lee, "Deep Learning-enabled Accurate and Interpretable Stress-strain Characterization from Ultrasonic Measurements", International Journal of Mechanical Sciences, 110695, 2025 (IF=9.4, JCR Top 2.5%) [Link]
  5. Sooyoung Lee, Jihun Lee, Joong Seok Lee, and Seungchul Lee, "Deep Learning-accelerated Multiple Design Generation for Sound-absorbing Metaporous Materials", Engineering Applications of Artificial Intelligence 156, 111172, 2025 (IF=8.0, JCR Top 2.6%) [Link]
  6. Anton Nailevich Gafurov+, Sooyoung Lee+, Uzair Ali, Muhammad Irfan, Inyoung Kim, and Taik-Min Lee, "AI-driven Digital Twin for Autonomous Web Tension Control in Roll-to-roll Manufacturing System", Scientific Reports 15 (1), 1-17, 2025 (JCR Top 18.1%) [Link]
  7. Jeongwoo Lee and Sooyoung Lee, "A Deep Generative Approach for Neural Augmentation of Heat Sink Surface Defects", International Journal of Precision Engineering and Manufacturing-Smart Technology 3, 151-159, 2025 [Editor-in-Chief's Choice] [Link]
  8. Jungsik Choi, Jeongmin Oh, Taeyoung Ko, Byunyoung Chung, Young-Chul Choi, Sooyoung Lee*, and Hyunseok Oh*, "Intelligent Metallic Loose Part Monitoring in Three-dimensional Structures using Convolutional Neural Networks and Position-invariant Loss Function", Nuclear Engineering and Technology, 103474, 2025 (JCR Top 15.9%) [Link]
  9. Sooyoung Lee, Choon-Su Park, Keonhyeok Park, Hyung Jin Lee, and Seungchul Lee, "A Physics-informed and Data-driven Deep Learning Approach for Wave Propagation and its Scattering Characteristics", Engineering with Computers 39 (4), 2609-2625, 2023 (IF=7.3, JCR Top 3.0%) [Link]
  10. Sooyoung Lee, Jihun Lee, Joong Seok Lee, and Seungchul Lee, "Deep Learning-based Prediction and Interpretability of Physical Phenomena for Metaporous Materials", Materials Today Physics 30, 100946, 2023 (IF=11.5, JCR Top 8.4%) [Link]
  11. Seongwook Choi+, Jinge Yang+, Sooyoung Lee+, Jiwoong Kim, Jihye Lee, Won Jong Kim, Seungchul Lee, and Chulhong Kim, "Deep Learning Enhances Multiparametric Dynamic Volumetric Photoacoustic Computed Tomography In Vivo (DL‐PACT)", Advanced Science 10 (1), 2202089, 2023 (IF=15.1, JCR Top 6.8%) [Featured as a Cover Article] [Link]
  12. Iljoo Jeong, Sooyoung Lee, Keonhyeok Park, Iljeok Kim, Hyunsuk Huh, and Seungchul Lee, "Wafer Map Failure Pattern Classification using Geometric Transformation-invariant Convolutional Neural Network", Scientific Reports 13 (1), 8127, 2023 (JCR Top 18.3%) [Link]
  13. Keonhyeok Park, Jong Young Lee, Sooyoung Lee, Iljoo Jeong, Seo-Yeon Park, Jin Won Kim, Sun Ah Nam, Hyung Wook Kim, Yong Kyun Kim, and Seungchul Lee, "Deep Learning Predicts the Differentiation of Kidney Organoids derived from Human-induced Pluripotent Stem Cells", Kidney Research and Clinical Practice 42 (1), 75, 2023 (JCR Top 15.4%) [Link]
  14. Hyeonji Kim, Keonhyeok Park, Jung-Min Yon, Sung Won Kim, Sooyoung Lee, Iljoo Jeong, Jinah Jang, Seungchul Lee, and Dong-Woo Cho, "Predicting Multipotency of Human Adult Stem Cells derived from Various Donors through Deep Learning", Scientific Reports 12 (1), 21614, 2022 (JCR Top 18.3%) [Link]
  15. Bayu Adhi Tama, Sooyoung Lee, and Seungchul Lee, "A Systematic Mapping Study and Empirical Comparison of Data-driven Intrusion Detection Techniques in Industrial Control Networks", Archives of Computational Methods in Engineering 29 (7), 5353-5380, 2022 (IF=9.7, JCR Top 0.5%) [Link]
  16. Sooyoung Lee, Jiho Chang, and Seungchul Lee, "Point-level Deep Learning Approach for 3D Acoustic Source Localization", Smart Structures and Systems 29 (6), 777-783, 2022 (JCR Top 19.5%) [Link]
  17. Sooyoung Lee, Jiho Chang, and Seungchul Lee, "Deep Learning-enabled High-resolution and Fast Sound Source Localization in Spherical Microphone Array System", IEEE Transactions on Instrumentation and Measurement 71, 1-12, 2022 (IF=5.9, JCR Top 8.2%) [Link]
  18. Sooyoung Lee, Jiho Chang, and Seungchul Lee, "Deep Learning-based Method for Multiple Sound Source Localization with High Resolution and Accuracy", Mechanical Systems and Signal Processing 161, 107959, 2021 (IF=8.9, JCR Top 2.5%) [National Top 10 Mechanical Technologies] [Link]
  19. Andrew Glaeser, Vignesh Selvaraj, Sooyoung Lee, Yunseob Hwang, Kangsan Lee, Namjeong Lee, Seungchul Lee, and Sangkee Min, "Applications of Deep Learning for Fault Detection in Industrial Cold Forging", International Journal of Production Research 59 (16), 4826-4835, 2021 (IF=9.0, JCR Top 6.3%) [Link]
  20. Gyuwon Kim, Sooyoung Lee, Jong-Seok Oh, and Seungchul Lee, "Deep Learning-based Estimation of the Unknown Road Profile and State Variables for Vehicle Suspension System", IEEE Access 9, 13878-13890, 2021 [Link]
  21. Sooyoung Lee, Seokyeong Byeon, Hyoung Seop Kim, Hyungyu Jin, and Seungchul Lee, "Deep Learning-based Phase Prediction of High-entropy Alloys: Optimization, Generation, and Explanation", Materials & Design 197, 109260, 2021 (IF=9.4, IF=16.6%) [Link]
  22. Kyung Ho Sun, Hyunsuk Huh, Bayu Adhi Tama, Sooyoung Lee, Joon Ha Jung, and Seungchul Lee, "Vision-based Fault Diagnostics using Explainable Deep Learning with Class Activation Maps", IEEE Access 8, 129169-129179, 2020 [Link]
  23. Sooyoung Lee, Bayu Adhi Tama, Changyun Choi, Jong-Yeon Hwang, Jonggeun Bang, and Seungchul Lee, "Spatial and Sequential Deep Learning Approach for Predicting Temperature Distribution in a Steel-making Continuous Casting Process", IEEE Access 8, 21953-21965, 2020 [Link]
  24. Andrew Glaeser, Vignesh Selvaraj, Kangsan Lee, Namjeong Lee, Yunseob Hwang, Sooyoung Lee, Seungchul Lee, and Sangkee Min, "Remote Machine Mode Detection in Cold Forging using Vibration Signal", Procedia Manufacturing 48, 908-914, 2020 [Link]
  25. Sooyoung Lee, Bayu Adhi Tama, Seok Jun Moon, and Seungchul Lee, "Steel Surface Defect Diagnostics using Deep Convolutional Neural Network and Class Activation Map", Applied Sciences 9 (24), 5449, 2019 [Link]