권창현 (산업 및 시스템공학과) 

겸임교수

Office

E2-1, 4210호

Tel

3138

E-mail

chkwon@kaist.ac.kr

Site

Site Url

Summary

Research Interest

– Operations Research and Transportation Science
– Computational Optimization Methods
– Urban Mobility and Urban Logistics Systems
– Machine Learning for Mathematical Optimization

Education

– 2000, KAIST, Mechanical Engineering, B.S.
– 2005, Pennsylvania State University, Industrial Engineering & Operations Research, M.S.
– 2008, Pennsylvania State University, Industrial Engineering, Ph.D.

Biography

Changhyun Kwon (권창현) is an Associate Professor in Industrial and Systems Engineering at KAIST and the director of the Computational Optimization Methods (COMET) Lab. He is also an affiliated faculty member of the Cho Chun Shik Graduate School of Mobility at KAIST. His research goal is to advance computational optimization methods for efficient operations of current and future transportation and logistics systems. His research has been supported by various organizations, including the National Research Foundation of Korea, the National Science Foundation, the U.S. Department of Transportation, and the Canadian Embassy. He received a Ph.D. in Industrial Engineering in 2008 and an M.S. in Industrial Engineering and Operations Research in 2005, both from the Pennsylvania State University. H e also received a B.S. in Mechanical Engineering from KAIST in 2000. He received the NSF CAREER award in 2014. Before he joined KAIST in 2023, he was at the University at Buffalo, where he received the UB Exceptional Scholar: Young Investigator Award in 2015, and the University of South Florida. He is an active member of INFORMS and TRB.

Publication

  • Bogyrbayeva, A., T. Yoon, H. Ko, S. Lim, H. Yun, C. Kwon. (2023) A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone. Transportation Research Part C: Emerging Technologies, 148, 103981
  • Bogyrbayeva A., S. Jang, A. Shah, Y. J. Jang, C. Kwon. (2022) A Reinforcement Learning Approach for Rebalancing Electric Vehicle Sharing Systems. IEEE Transactions on Intelligent Transportation Systems, 23(7), 8704–8714.
  • Takalloo, M., C. Kwon (2020). On the Price of Satisficing in Network User Equilibria. Transportation Science, 54(6), 1555–1570.
  • Su. L., C. Kwon. (2020) Risk-Averse Network Design with Behavioral Conditional Value-at-Risk for Hazardous Materials Transportation. Transportation Science, 54(1), 184–203.
  • Sun, L., M. Karwan, C. Kwon (2018). Generalized Bounded Rationality and Robust Multicommodity Network Design. Operations Research, 66(1), 42–57.
  • Esfandeh, T., R. Batta, and C. Kwon (2018). Time-Dependent Hazardous-materials Network Design Problem. Transportation Science, 52(2), 454–473.
  • Zhang, A., J.E. Kang, C. Kwon (2017). Incorporating Demand Dynamics in Multi-Period Capacitated Fast-charging Location Planning for Electric Vehicles. Transportation Research Part B: Methodological, 103, 5–29.
  • Sun, L., M. Karwan, and C. Kwon (2016). Robust Hazmat Network Design Problems Considering Risk Uncertainty. Transportation Science, 50(4), 1188–1203.
  • Toumazis, I. and C. Kwon (2016). Worst-case Conditional Value-at-Risk Minimization for Hazardous Materials Transportation. Transportation Science, 50(4), 1174–1187.
  • Kumar, A. A., J. E. Kang, C. Kwon, and A. Nikolaev (2016). Inferring Origin-Destination Pairs and Utility-Based Travel Preferences for Shared Mobility Systems Users in a Multi-Modal Environment. Transportation Research Part B: Methodological, 91, 270–291.
  • Esfandeh, T., C. Kwon, R. Batta (2016). Regulating Hazardous Materials Transportation by Dual Toll Pricing. Transportation Research Part B: Methodological, 83, 20–35.
  • Friesz, T. L., T. I. Kim, C. Kwon and M. A. Rigdon (2011). Approximate Network Loading and Dual Time Scale Dynamic User Equilibrium. Transportation Research Part B: Methodological, 45(1), 176-207.

Awards

Research

  • 2015—2023, Associate Professor, University of South Florida
  • 2008—2015, Assistant Professor, University at Buffalo

Teaching

Students

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