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기형선
Ki, Hyungson

기형선

Department of Mechanical Engineering(기계공학과)

  • Laser Processing and Artificial Intelligence Lab.
  • Website
Research Interests
Laser Processing;Artificial Intelligence;AI;레이저 가공;인공지능;레이저 용접;레이저 열처리;레이저 정밀가공
Lab Description
In this laboratory, we have been researching various laser processing technologies including macro processing technologies such as laser heat treatment, laser welding, and laser cladding, ultra-precision processing using lasers, and dual-beam pulsed laser deposition technology. Recently, we are focusing on research to advance laser processing technology using artificial intelligence technology. We are striving to cultivate researchers that fit the trend of the times while developing leading laser processing technology by using AI extensively.
Researcher ID Research Gate ORCiD Scopus Google Scholar
Previous
Prediction of surface reflectance using a deep learning model trained on synthetic surface images File

Yoo, Jeonghyun , Ki, Hyungson

Article Issue Date2024-07 View25
Deep learning-based prediction of thermal residual stress and melt pool characteristics in laser-irradiated carbon steel File

Woo, Myungrin , Ki, Hyungson

Article Issue Date2024-06 View24
Deep learning-based monitoring system for predicting top and bottom bead widths during the laser welding of aluminum alloy File

Nam, Kimoon , Ki, Hyungson

Article Issue Date2024-06 View38
Femtosecond laser-treated copper sintering surface to enhance pool boiling heat transfer File

Lee, Seunghwan , Kim, Yeonsu , Ki, Hyungson , Lee, Jaeseon

Article Issue Date2024-03 View25
Pool-boiling enhancement on periodic micro/nano ripple-structured surfaces fabricated by femtosecond laser File

Lee, Seunghwan , Kim, Yeonsu , Ki, Hyungson , Lee, Jaeseon

Article Issue Date2023-11 View27
Deep-learning model for predicting hardness and phase distributions from two cross-sectional temperature distribution images in laser heat treatment of AH36 steel File File

Son, Myeonggyun , Ki, Hyungson

Article Issue Date2023-11 View22
One camera-based laser keyhole welding monitoring system using deep learning File

Nam, Kimoon , Ki, Hyungson

Article Issue Date2023-10 View13
Deep-learning approach for predicting crystalline phase distribution of femtosecond laser-processed silicon File File

Kim, Hyun Kyung , Woo, Myungrin , Ki, Hyungson

Article Issue Date2023-02 View41
Prediction of surface morphology and reflection spectrum of laser-induced periodic surface structures using deep learning File

Na, Hojun , Yoo, Jeonghyun , Ki, Hyungson

Article Issue Date2022-12 View24
Investigation of microstructure and residual stress development during laser surface melting of AH36 steel using 3-D fully coupled numerical model File

Yeo, Haram , Son, Myeonggyun , Ki, Hyungson

Article Issue Date2022-11 View24
Enhancement of flow boiling heat transfer by laser-induced periodic surface structures using femtosecond laser File

Lim, Kihoon , Lee, Keunhee , Ki, Hyungson , Lee, Jaeseon

Article Issue Date2022-11 View57
Analysis of laser-beam absorptance and keyhole behavior during laser keyhole welding of aluminum alloy using a deep-learning-based monitoring system File

Kim, Hyeongwon , Nam, Kimoon , Kim, Yeonsu , Ki, Hyungson

Article Issue Date2022-08 View32
Accurate prediction of the particle image velocimetry flow field and rotor thrust using deep learning File

Oh, Sehyeok , Lee, Seungcheol , Son, Myeonggyun , Kim, Jooha , Ki, Hyungson

Article Issue Date2022-03 View38
Prediction of structural deformation of a deck plate using a GAN-based deep learning method File

Oh, Sehyeok , Jin, Hyung Kook , Joe, Seok Je , Ki, Hyungson

Article Issue Date2021-11 View31
Deep-learning-based real-time monitoring of full-penetration laser keyhole welding by using the synchronized coaxial observation method File

Kim, Hyeongwon , Nam, Kimoon , Oh, Sehyeok , Ki, Hyungson

Article Issue Date2021-08 View25
Enhancing coupling efficiency in laser keyhole welding of copper using femtosecond laser surface modification File

Lee, Keunhee , Ki, Hyungson

Article Issue Date2021-07 View40
Deep-learning approach for predicting laser-beam absorptance in full-penetration laser keyhole welding File File

Oh, Sehyeok , Kim, Hyeongwon , Nam, Kimoon , Ki, Hyungson

Article Issue Date2021-06 View17
Deep-Learning Approach to the Self-Piercing Riveting of Various Combinations of Steel and Aluminum Sheets File File

Kim, Hyun Kyung , Oh, Sehyeok , Cho, Keong-Hwan , Kam, Dong-Hyuck , Ki, Hyungson

Article Issue Date2021-05 View30
Unified momentum equation approach for fluid-structure interaction problems involving linear elastic structures File

Yeo, Haram , Ki, Hyungson

Article Issue Date2020-08 View28
Tunable wetting surfaces with interacting cavities via femtosecond laser patterning and wet etching File

Deng, Chun , Ki, Hyungson

Article Issue Date2020-07 View21
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