Woosung Choi earned a B.S. degree from Inha University (Summa Cum Laude) in Incheon, Republic of Korea, in 2003. He then obtained an M.S. degree from KAIST in Daejeon, Republic of Korea, in 2005. Finally, he completed his Ph.D. degree at Seoul National University in Seoul, Republic of Korea, in 2018. Currently, he serves as a principal researcher at KEPCO Research Institute in Daejeon, South Korea. His responsibilities include life and risk assessment for power plants and the development of national standards for the power generation industry (Korea Electric Power Industry Code). His research interests encompass prognostics and health management, multi-fidelity analysis with FEA, and deep learning analysis.
In particular, Woosung has developed various condition diagnosis and prediction solutions using machine learning and deep learning in the energy field. Some of these solutions are currently applied at power plant sites, while others are utilized by small and medium-sized businesses. His practical experience in international cooperation includes planning and conducting joint research in the energy field with Fraunhofer (since 2019) and Siemens (since 2020) in Germany, as well as EPRI (since 2017) and SwRI (from 2009 to 2012) in the United States. Additionally, he successfully applied research results to power plant sites following an assignment from Malaysia TNBR (in 2016).
After completing a two-year assignment at EPRI, he currently serves as the team leader for the R&D Business Team in the Research Strategy Division since 2024. His responsibilities include R&D performance analysis, R&D commercialization, promotion, and external collaboration. Especially, He excels in R&D planning and executing events based on universal curiosity.
He believes that the completion of technology lies in standards. As a member of the Maintenance and Repair Subcommittee of the Korea Electric Association, he develops industrial technical standards related to risk assessment and life evaluation of power systems. Additionally, as a member of the ASME PCC committee, he strives to incorporate the technical standards developed in Korea into the ASME code.
Woosung’s perspective emphasizes people over technology. While studying system integrity evaluation, he also serves as a board member of AI Friends (AI Research Society) at Daedeok Science Complex."
Instructor-Led DLI workshops for academia
Fundamental of Deep Learning
Applications of AI for Anomaly Detection
Applications of AI forPredictive Maintenance
EPRI (USA): Energy AI / Digital twin for gas turbine / Reliability of wind turbine (2021.8~2023.8) Visiting Scientist
Fraunhofer ISC/HTL (Germany): Development of multi-sensing packages for oxy-GT & GT (2019~2022)
SIEMENS AG (Germany): AI-based performance optimization solution for GT (2020~2021)
EPRI (USA): Computational analysis for repairing guidelines of gas turbine (2018~2019)
University of Florida (USA) : Bayesian inference, Surrogate modeling (2016)
TNBR (Malaysia): Health monitoring system for high-temperature power piping (2016~2017), assignment
SwRI (USA): Life assessment for gas turbine blade/vane based on FSI methodologies (2009~2011)
CRIEPI & Meijo univ. & Toshiba & HITACHI (Japan): Life assessment for steam turbine (2007~2009)
MPA (Germany): Risk-based maintenance for power plant (2006)
Hot part management system for gas turbine, C-2019-029975
Deep learning-based degradation evaluation solution, C-2019-015964 (Technology transfer)
Data pre-processing SW for turbomachinery, C-2019-015963
Deep learning-based diagnosis solution for turbomachinery, C-2019-015962
Deep learning-based GT anomaly detection solution, C-2019-015961
Machine learning-based degradation evaluation solution, C-2018-040440 (Technology transfer)
Advanced Life Assessment System Plus RBM, C-2016-023728
Reliability Evaluation System Tool, C-2014-011959
BLAST : Blade Life Assessment System Tool, C-2014-011957
DEST : Degradation Evaluation System Tool for turbine, C-2013-019048
ATLAS mini ver.2, C-2013-019045
TPES : Turbine Performance Evaluation System, C-2013-019044
THIS plus :Turbine Hybrid Information System. Plus, C-2012-017416
THIS : Turbine Hybrid Informatio System, C-2012-017415
Virtu :Virtual Turbine, C-2012-017414
iLAS(indentation based turbine Life assessment system) S-2010-004104