Faculty Research Profile
Im Doo Jung
학력
· 2012 - 2016: Ph.D. Mechanical Engineering, Pohang University of Science and Technology (POSTECH)
· 2003 - 2011: B.S. Mechanical Engineering, Pohang University of Science and Technology (POSTECH)
주요 경력
· 2024 - Present: Associate Professor, Department of Mechanical Engineering, UNIST, South Korea
· 2020 - 2024: Assistant Professor, Department of Mechanical Engineering, UNIST, South Korea
· 2017 - 2020: Senior Researcher, 3D Printing Materials Center, Korea Institute of Materials Science (KIMS), Korea
· 2016 - 2017: Postdoc., School of EEE, Nanyang Technological University, Singapore
· 2015: Visiting Researcher, Dept. Of Mechanical Engineering, TU/e, Eindhoven, Netherlands
수상/학회/외부활동
· PHM 학회 총무이사
General Affairs Director, Korean Society for Prognostics and Health Management (PHM), Korea
· 대한기계학회 울산지회 재무이사
Finance Director, Ulsan Branch, Korean Society of Mechanical Engineers (KSME), Korea
· 대한기계학회 생산 및 설계 부문 미래발전위원
Future Development Committee, Production and Design Engineering Division, Korean Society of Mechanical Engineers (KSME), Korea
· 한국분말재료학회 평의원
Councilor, Korean Powder Metallurgy & Materials Institute (KPMI), Korea
지능형 생산 및 소재 연구실
Intelligent Manufacturing and Materials Lab
We create and apply new methods for digital transformation. The IMM Lab is an interdisciplinary research team devoted to developing and applying novel technologies for academic and economic breakthrough in manufacturing industry. Specifically, we develop a host of methods to enable meaningful data achievement from mechanical system, machine learning based new process, additively manufactured functional 3D & 4D system and digital twin. We are applying these digitalization technologies for highly efficient, functional and safe systems.
We create and apply new methods for digital transformation. The IMM Lab is an interdisciplinary research team devoted to developing and applying novel technologies for academic and economic breakthrough in manufacturing industry. Specifically, we develop a host of methods to enable meaningful data achievement from mechanical system, machine learning based new process, additively manufactured functional 3D & 4D system and digital twin. We are applying these digitalization technologies for highly efficient, functional and safe systems.
연구분야
Artificial Intelligence for Manufacturing, Material and Medical Innovation, Additive Manufacturing for Intelligent Metal Components, Digital Twin
Artificial Intelligence for Manufacturing, Material and Medical Innovation, Additive Manufacturing for Intelligent Metal Components, Digital Twin
연구 희망분야
Metaverse for Virtual Manufacturing, Blockchain for Safe Data Protection for Manufacturing
Metaverse for Virtual Manufacturing, Blockchain for Safe Data Protection for Manufacturing
연구주제
· Additive Manufacturing for IT integrated Metal Parts
· A.I. Augmented Metal Parts for Smart Mechanical System & Smart Factory
· Smart Self-Powered IoT Sensor Development for Remote Monitoring of Factory
· Intelligent Titanium Components Manufacturing for Smart Bio-Medical Implant
· Microstructural/Numerical Analysis for Manufacturing Process Verification
· Digital Twin, Metaverse for Advanced Maintenance of Mechanical System/Factory
· Additive Manufacturing for IT integrated Metal Parts
· A.I. Augmented Metal Parts for Smart Mechanical System & Smart Factory
· Smart Self-Powered IoT Sensor Development for Remote Monitoring of Factory
· Intelligent Titanium Components Manufacturing for Smart Bio-Medical Implant
· Microstructural/Numerical Analysis for Manufacturing Process Verification
· Digital Twin, Metaverse for Advanced Maintenance of Mechanical System/Factory
국가연구개발사업 기술 분류체계
국가과학기술표준분류
EA. 기계 > EA02. 생산기반기술 > EA0208. 컴퓨터통합생산시스템
논문
· Virtual Surface Morphology Generation of Ti-6Al-4V Directed Energy Deposition via Conditional Generative Adversarial Network, Virtual and Physical Prototyping (IF:10.962, JCR 5% in Engineering, Manufacturing), 2023
· Meniscus-guided Micro-printing of Prussian Blue for Smart Electrochromic Display, Advanced Science (IF:17.521, JCR 5% in Materials Science, Multidisciplinary), 2023
· Laser Powder Bed Fusion for AI Assisted Digital Metal Components, Virtual and Physical Prototyping (IF:10.962, JCR 5% in Engineering, Manufacturing), 2022