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Hyperautonomy Artificial Intelligence Lab

서울대학교 초자율화 인공지능 연구실

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RESEARCH

PROJECT

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  • Development of an Estimated Time of Arrival (ETA) Prediction Model and Framework for Robotic Parking…

    Period

    2026-07-01 ~ 2027-06-30

  • Manufacturing Task-Specific Foundation Models for a Full-Stack AI Factory

    Period

    2026-06-01 ~ 2031-02-28

  • AI-based OHT Routing Algorithm Development

    Period

    2026-05-01~2028-04-30

  • Development of Core Technologies for a PHM System for Fixed-Wing Aircraft Based on a System Lineage …

    Period

    2026-04-07~2026-12-31

  • Development of CBM+-based Anomaly Detection, Condition Diagnosis, and Degradation Prediction Technol…

    Period

    2026-03-19~2029-03-18

  • Safety Guardian Al Agent Using Four-Sense Sensor Data Quadruped Robot

    Period

    2026-01-01 ~ 2026-12-31

  • Development of a Chamberless Noise Diagnosis Algorithm

    Period

    2025-12-29 ~ 2026-09-30

  • Advancing Thermo-Mechanical Reliability in 2.xD/3D Packages using Physics-Informed AI and Generative…

    Period

    2025-10-01 ~ 2030-09-28

  • Development of a Virtual Process Control System Based on Operational Data for Digital Twin Environme…

    Period

    2025-09-29 ~ 2027-09-28

  • Development of Core Technologies for Manufacturing Foundation Models (MFM)

    Period

    2025-07-01 ~ 2028-01-31

  • Foundation of Next-generation Eco-friendly Secondary Battery Components to Strengthen Supply Chain

    Period

    2025-05-01 ~ 2028-12-31

  • Development and Demonstration of Purpose-Built Electric Vehicles Using Design Platforms

    Period

    2024-07-01 ~ 2027-12-31

HAI LAB

PUBLICATION

  • Deep Learning-based Rapid and Precise Die Design to Compensate Springback in Metallic Bipolar Plate Stamping for Proton Exchange Membrane Fuel Cells

    Hyeongmin Kim¹, Sangwook Langenstück-Lee¹, Donghyu Lee, Florian Hüsing, Henning Janssen, Christian Brecher*, and Byeng D. Youn*

    Measurement, SCIE (IF: 6.1, Rank: 10.4%), Vol. 290, pp. 122923
  • A Robust Deep Learning Framework for Weld Defect Classification in PAUT With Specimen-Level Preprocessing

    Jongheok Park, Donghyu Lee, Wonjae Choi, Byeng D. Youn*, and Jong Moon Ha*

    NDT & E International, SCIE (IF: 6.0, Rank: 9.5%), Vol. 164, pp. 103840
  • Frequency-Band Graph-based Sensor Fusion with Sensitivity-aware Energy Assist Network for Machinery System Fault Diagnosis

    Sang Kyung Lee, Hyeongmin Kim, Minseok Chae, Hansoo Kim, Joonho Yang, Heonjun Yoon*, and Byeng D. Youn*

    Engineering Applications of Artificial Intelligence , SCIE (IF: 9.0, Rank: 3.1%), Vol. 179, pp. 115273
  • Battery Maximum Available Capacity Estimation in Partial Charge Curve with Current Charge State Invariant Feature

    Bongmo Kim, Yong Chae Kim, Hyunhee Choi, Gyeong Ryun Gwon, Taejin Kim*, and Byeng D. Youn*

    Journal of Energy Storage, SCIE (IF: 10.7, Rank: 14.9%), Vol. 138, pp. 118726
  • Transformer-Based Prediction of Dispersion Relation and Transmittance in Phononic Crystals

    Donghyu Lee, Taehun Kim, Ju Hwan Han, Sayhee Kim, Byeng D. Youn*, and Soo-Ho Jo*

    International Journal of Mechanical Sciences, SCIE (IF: 11.4, Rank: 1.9%), Vol. 307, pp. 110880
  • Steering of Multiple Defect Bands in One-dimensional Phononic Crystals with Segmented Piezoelectric Defects

    Soo-Ho Jo¹, Taehun Kim¹, Donghyu Lee, Pengpeng Yu, Junlei Wang, Byeng D. Youn, and Heonjun Yoon*

    Journal of Physics D-Applied Physics, SCIE (IF: 3.2, Rank: 44.8%), Vol. 58, No. 46 pp. 465501
  • Deep Learning-Enabled Diagnosis of Abdominal Aortic Aneurysm Using Pulse Volume Recording Waveforms: An In-Silico Study

    Sina Masoumi Shahrbabak, Byeng D. Youn, Hao-Min Cheng, Chen-Huan Chen, Shih-Hsien Sung, Ramakrishna Mukkamala, and Jin-Oh Hahn*

    Sensors, SCIE (IF: 4.0, Rank: 29.0%), Vol. 25, No. 21 pp. 6678
  • Time-Domain Signal Denoising and Expert Decision-Support Visualization with AttenTDNet for High-Voltage Power-Cable Joint-Box Monitoring

    Jingyo Jeong, Jeong H. Choi, Wongon Kim*, and Byeng D. Youn *

    Electrical Engineering, SCIE (IF: 2.7, Rank: 50.3%), Vol. 108, pp. 364