About
Profile
Dr. YongKyung Oh serves as a visiting researcher at the University of California, Los Angeles (UCLA) Health - David Geffen School of Medicine. He contributes as a member of the UCLA Medical & Imaging Informatics group, under the leadership of Dr. Alex Bui. Simultaneously, he holds a postdoctoral researcher position at the Industry Intelligentization Institute at the Ulsan National Institute of Science and Technology (UNIST). He received his Ph.D. in Industrial Engineering from UNIST, under the supervision of Dr. Sungil Kim. Prior to pursuing his Ph.D., he earned his Master's degree in Technology and Innovation Management and his B.Sc. in Physics, both from UNIST.
His research focuses on developing and applying domain-specific machine learning and deep learning techniques to address complex real-world problems across a diverse range of fields. This interdisciplinary approach spans multiple sectors, including medical, healthcare, manufacturing, energy, transportation, maritime operations, logistics, supply chain and so forth. His proficiency encompasses domain-specific AI techniques, and he provides insightful perspectives on practical implementations.
In addition to his academic pursuits, he has gained valuable industry experience through visiting researcher positions at Carnegie Mellon University (CMU), General Motors (GM) Global R&D Center, and the Institute of Theoretical Physics and Astrophysics (ITAP) of Kiel University, Germany. Furthermore, he has participated in student consulting projects for companies including CSL Behring, IBM, and Deere&Company.
His research focuses on developing and applying domain-specific machine learning and deep learning techniques to address complex real-world problems across a diverse range of fields. This interdisciplinary approach spans multiple sectors, including medical, healthcare, manufacturing, energy, transportation, maritime operations, logistics, supply chain and so forth. His proficiency encompasses domain-specific AI techniques, and he provides insightful perspectives on practical implementations.
In addition to his academic pursuits, he has gained valuable industry experience through visiting researcher positions at Carnegie Mellon University (CMU), General Motors (GM) Global R&D Center, and the Institute of Theoretical Physics and Astrophysics (ITAP) of Kiel University, Germany. Furthermore, he has participated in student consulting projects for companies including CSL Behring, IBM, and Deere&Company.
Work Experiencecs
UCLA Health - David Geffen School of Medicine (Los Angeles, CA, US): Visiting researcher, 2023 ~
- Contribute as a member of the UCLA Medical & Imaging Informatics group, under the leadership of Dr. Alex Bui
UNIST Industry Intelligentization Institute (Ulsan, Korea): Postdoctoral researcher, 2023 ~
- Contribute as a member of the UNIST Data Analytics Lab, under the leadership of Dr. Sungil Kim
UNIST Data Analytics Lab (Ulsan, Korea): Graduate researcher & Laboratory Leader, 2018 ~ 2022
- Advisor: Prof. Sungil Kim | Department of Industrial Engineering
Carnegie Mellon University (Pittsburgh, PA, US): Visting Researcher, 2020
- High-Potential Individuals Global Training Program fully supported by IITP and Korean Government.
- Attend core courses and conduct project-based on IoT, machine learning, and deep learning.
- CMU Studio Project: Conversational Chatbot. [demo]
General Motors Global Technology Center (Detroit, MI, US): Visting Researcher, 2017
- Mentor: Dr. Wayne Cai / Research support for automotive manufacturing operation
- Perform analytical analysis using experimental data. Develop a multi-platform welding simulation tool for GM internal users. [demo]
Accenture Korea (Seoul, Korea): Research Assistant, 2016
- Lotte Duty Free Shop – New Generation System Integration Project
- Work support for the planning team, translation, and PMO (project management office)
Institute of Theoretical Physics and Astrophysics (ITAP), CAU, (Kiel, Germany): IAESTE Research Intern, 2014
- Mentor: Prof. Sebastian Wolf / Astrophysics- Mechanism of Interstellar Dust Alignment
- IAESTE internship / Conduct simulations and code analysis with C and Fortran
Academic Backgroud
Ph.D. in Industrial Engineering at UNIST, 2023
- Thesis: A Comprehensive Study of Deep Learning for Real-World Multivariate Time Series Classification
- Advisor: Sungil Kim
M.S. in Technology and Innovation Management at UNIST, 2017
- Management of Technology (MOT) degree, Association to Advance Collegiate Schools of Business (AACSB) certified
- Dissertation Paper (Capstone Project): Discussion of the meaning and components of the fourth industrial revolution, and recommendations for Korea to prepare for the fourth industrial revolution
- Advisor: KwangWook Gang
B.S. in Natural science at UNIST, 2015
- Major – Physics
- Double Minor – Mechanical Engieering & Advanced Material Science
- Valedictorian, Magna cum Laude, Accomplished total 181 credits
Scholarship & Fellowship
- Biomedical UniStar Training Program, Visiting research program for the collaborative research between UNIST and UCLA School of Medicine, fully supported by Korea Health Industry Development Institute KHIDI, 2023-2024
- UNIST Graduate Scholarship (Ph.D. degree), UNIST, 2018-2022
- High-Potential Individuals Global Training Program, fully supported by IITP & Ministry of Science, ICT and Future Planning, 2020
- FISITA Travel Bursary Scholarship, FISITA - International Federation of Automotive Engineering Societies, 2017
- UNIST - GM Internship Fellowship, UNIST, General Motors, 2017
- UNIST Graduate Scholarship (Master degree), UNIST, 2015-2016
- UNIST Undergraduate Scholarship, UNIST, 2011-2014
Competition Award
- Best study, Medical Informatics Homecoming Day, Asan Medical Center & Ministry of Health and Welfare, 2023
- 1st place, Professional Training for Medical Data Analysis, Asan Medical Center & Ministry of Health and Welfare, 2020
- 2nd place in the Medical Startup Festa, Center for Creative Economy and Innovation, Ulsan, 2018
- 1st place (Minister Award) in the Korea R&D Festival – KOREA MOTIE, KIAT, Ministry of Trade, Industry and Energy, 2017
Teaching Experiences
- (Spring-Fall, 2021) Undergraduate Interdisciplinary Research Project | Teaching Assistant
- Research Topic: Data analytics and statistical modeling for traffic congestion propagation
- Advise overall project and presentation. Featured undergraduate student research at KIIE Fall Conference
- Yeo J., Seo H., and Shim S., "A Methodology for Predicting Traffic Accidents Using Road Network Structure", KIIE Fall Conference, November 2021
- (Fall 2019) MGT205, Financial Accounting | Teaching Assistant
- (Fall 2019) MGT206, Managerial Accounting | Teaching Assistant
- (Fall, 2018) MGT206, Managerial Accounting | Teaching Assistant
- (Spring, 2018) MGE362, Quality Management | Teaching Assistant
- (Fall, 2017) TIM614, Integration of IT, Manufacturing, and Operational Systems | Teaching Assistant
- (Spring, 2016) MGT473, Entrepreneurship and Venture Management | Teaching Assistant
- (Fall, 2015) AHS230, Recent Trends in Science and Technology Business of Korea | Teaching Assistant
- (Spring, 2015) MGT410, Psychology and Marketing | Teaching Assistant