Faculty 교수진 We are the Frontiers of Liberty, Justice and Truth


Joonyup Eun
기술경영학과  은준엽 부교수 Joonyup Eun

Data-Driven Modeling and Analysis of Service Delivery Systems

Deterministic/Stochastic Modeling and their Applications in Service Operations

Capacity Planning/Management for Industrial Applications

Development of Optimization Methodologies : Stochastic Integer Programming (Sample Average Approximation), Benders Decomposition, Branch-and-Bound, Dynamic Programming, Meta-Heuristics, Quantum-Inspired Heuristics, Simulation







Korea University, Seoul, Korea (B.Eng. Industrial Systems and Information Engineering)

Korea Advanced Institute of Science and Technology(KAIST), Daejeon, Korea (M.S. Industrial and Systems Engineering)

Purdue University, West Layfayette, IN, USA (Ph.D. Industrial Engineering)


고려대학교 기술경영전문대학원 기술경영학과 주임교수, Seoul, Korea

고려대학교 기술경영전문대학원 기술경영학과 조교수, 부교수, Seoul, Korea

PostDoctoral Research Fellow, Department of Anesthesiology, School of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

Data Science Fellow, Data Science Visions Trans-Institutional Program, Vanderbilt University, Nashville, TN, USA

  • Cha, H., Kim, D., Eun, J. *, and Cheong, T. *, 2023, Collaborative Traveling Salesman Problem with Ground Vehicle as a Charger for Unmanned Aerial Vehicle. Transportation Letters−The International Journal of Transportation Research, 15(7), pp. 707-721. (SSCI/SCIE)
  • Eun, J., Tiwari, V.*, and Sandberg, W. S., 2022. Predicting Daily Surgical Volumes Using Probabilistic Estimates of Providers’ Future Availability. Decision Sciences, 53(1), pp. 124-149. (SSCI, Nominated as one of three finalists for the 2023 best paper award at Decision Sciences)
  • Kim, E., Han, K.S., Cheong, T., Lee, S.W., Eun, J.*, and Kim, S.J. *, 2022. Analysis on Benefits and Costs of Machine Learning-Based Early Hospitalization Prediction. IEEE Access, 10, pp. 32479-32493. (SCIE)
  • Yuh, J., Eun, J.*, and Cheong, T.*, 2021. Integer Programming Approach -and Application of Reformulation-Linearization Technique to Live Exchange Problem. Expert Systems with Applications, 185, 115599. (SCIE)
  • Jeon, A., Kang, J., Choi, B., Kim, N., Eun, J.*, and Cheong, T.*, 2021. Unmanned Aerial Vehicle Last-Mile Delivery Considering Backhauls. IEEE Access, 9, pp. 85017-85033. (SCIE)
  • Eun, J., Kim, S.P., Yih, Y., and Tiwari, V., 2019. Scheduling Elective Surgery Patients Considering Time-Dependent Health Urgency: Modeling and Solution Approaches. Omega−The International Journal of Management Science, 86, pp. 137-153. (SSCI/SCIE)
  • Eun, J., Song, B.D., Lee, S., and Lim, D.E., 2019. Mathematical Investigation on the Sustainability of UAV Logistics. Sustainability, 11(21), 5932. (SSCI/SCIE)
  • Choi, C.H., Eun, J., Cao, J., Lee, S., and Zhao, F., 2018. Global Strategic Level Supply Planning of Materials Critical to Clean Energy Technologies – A Case Study on Indium. Energy, 147, pp. 950-964. (SCIE)
  • Eun, J., Lee, S., and Yih, Y., 2017. Patient Appointment Scheduling, in Li, J., Kong, N., and Xie, X. (Eds), Stochastic Modeling and Analytics in Healthcare Systems (pp. 1-30), World Scientific Publishing. (Invited and peer-reviewed. Lead article of the book)
  • Eun, J., Sung, C.S, and Kim, E.S., 2017. Maximizing Total Job Value on a Single Machine with Job Selection. Journal of the Operational Research Society, 68(9), pp. 998-1005. (SSCI/SCIE)
  • Lee, J., Park, K., and Eun. J.*, 2021. Generative Adversarial Network (GAN) Based Image Augmentation for Casting Data Classification Enhancement. Korean Journal of Logistics, 29(4), pp.25-34. (KCI)
  • Lee, H.J., Hangbo, Y.*, and Eun, J.*, 2021. A Study on the Angel Educational Program Design using QFD and Benchmarking. Productivity Review, 35(2), pp. 163-203. (KCI)

Please visit https://solab.korea.ac.kr for other activities.


Systems Analytics and Smart Operations 분야는 다양한 산업의 운용 이슈를 시스템적 관점에서 분석하고, 주어진 사회적/경제적 조건 하에서 달성 가능한 최적의 목표를 이루기 위한 의사결정론에 대해서 연구한다.

산업 도메인에 대한 지식을 바탕으로 시스템적 관점에서 모델링을 시행하고, 해당 시스템을 개선할 수 있는 해를 도출하기 위해 결정론적/확률적 정수계획법, 스케쥴링, 메타휴리스틱, 시뮬레이션, 양자 인스파이어드 휴리스틱, 머신러닝, 딥러닝 등의 방법론을 활용한다.