Ph.D. Students
He is a graduate student in the Department of Industrial Engineering at Pusan National University, with a focus on AI applications and methods in various industries, including manufacturing, healthcare, defense, and finance. He is pursuing an MS-Ph.D. integrated course under the supervision of Professor Ki-Hun Kim. His research involves developing advanced AI methods to optimize industrial processes and enhance decision-making capabilities. He earned his B.S. in the Department of Industrial Engineering from Pusan National University in 2022, where he researched AI for personalized healthcare as an undergraduate research assistant.
He is a graduate student in the Department of Aerospace Engineering at Pusan National University, with a focus on AI applications and methods in defense industries. He is currently pursuing his Ph.D. degree under the supervision of Professor Ki-Hun Kim. His research involves developing advanced AI methods, focusing on Physics-Informed Neural Networks (PINNs), to optimize industrial processes and enhance decision-making capabilities. His research specifically targets the design of loss functions, optimization techniques, convergence, stability analysis, and neural architecture innovation within PINNs.
He is a graduate student in the Department of Industrial Engineering at Pusan National University, focusing on AI applications and methods in various industries, including defense, healthcare, safety, and finance. He is pursuing an integrated MS-Ph.D. program under the supervision of Professor Ki-Hun Kim. His research involves developing advanced AI methods to optimize industrial processes and enhance decision-making capabilities. Gyeong-Pil earned his B.S. in Industrial Engineering from Pusan National University in 2023, where he researched AI for personalized finance as an undergraduate research assistant.
He is a graduate student in the Department of Industrial Engineering at Pusan National University, with a focus on AI applications and methods in various industries, including manufacturing, healthcare, defense, and finance. He earned his B.S. in Industrial Engineering from Pusan National University in 2024. Prior to his advanced studies, he gained two years of professional experience in the Project Management Department at SAMSUNG E&A. Currently, he is pursuing an MS-Ph.D. integrated course under the supervision of Professor Ki-Hun Kim. His current research interests center on Large Language Models (LLMs) and developing advanced AI methods to optimize industrial processes and enhance decision-making capabilities.
She is a Ph.D. student in the Department of Industrial Engineering at Pusan National University, focusing on AI applications and methods in various industries, including manufacturing, finance, and healthcare. She is pursuing her Ph.D. degree under the supervision of Professor Ki-Hun Kim. Her research involves developing advanced AI methods to optimize industrial processes and enhance decision-making capabilities. Prior to pursuing her doctoral degree, she built professional expertise as a researcher at the Korea Energy Economics Institute, where she focused on GHG inventory, and climate change policies. She earned her Master’s degree in Business Analytics from Ulsan National Institute of Science and Technology, where she developed a foundation in data science and its strategic applications.
M.S. Students
He is a graduate student in the integrated Bachelor's and Master's program in the Department of Industrial Engineering at Pusan National University. His research focuses on AI applications and methodologies across various industries, including healthcare, defense, and finance. Under the supervision of Professor Ki-Hun Kim, he is developing advanced AI methodologies for Voice of Customer (VoC) analysis in the finance sector and topic modeling in the healthcare sector. He received his Bachelor's degree in Industrial Engineering from Pusan National University in 2024. Now, he is researching Large Language Models (LLMs).
She is a graduate student in the integrated Bachelor’s and Master’s program in the Department of Industrial Engineering at Pusan National University. Her research explores AI methodologies across diverse industrial domains, including manufacturing and port logistics, with the goal of optimizing operational processes and enhancing data-driven decision-making. Her current work focuses on developing trustworthy and interpretable AI methodologies, with a particular emphasis on spatio-temporal modeling and explainable artificial intelligence (XAI).
He is an undergraduate student in the Department of Industrial Engineering at Pusan National University and an undergraduate researcher supervised by Professor Ki-Hun Kim. He studies AI applications and methodologies across various industries, with current research focusing on quantum circuit optimization using reinforcement learning for industrial applications and on developing reliable deep learning models.
She is an undergraduate student in the Department of Mathematics at Pusan National University. As an undergraduate researcher under the supervision of Professor Ki-Hun Kim, she is researching AI applications and methodologies across various industries. Her current research focuses on expanding the practical applicability of explainable Artificial Intelligence (XAI) for industrial applications and developing reliable deep learning models.
She is an undergraduate student in the Department of Industrial Engineering at Pusan National University. Currently an intern under the supervision of Professor Ki-Hun Kim, she is mastering the fundamental principles of Artificial Intelligence and deep learning. Her current focus is on building solid research capabilities by exploring the architectures of deep learning models and their practical applications across various industrial sectors.
Alumni
M.S. : Industrial Engineering,
Pusan National University, 2026
B.S. : Industrial Engineering,
Pusan National University, 2024
M.S. : Industrial Engineering,
Pusan National University, 2026
B.S. : Industrial Engineering,
Pusan National University, 2024