Jinwoo Lee 

Office

F434

Tel

1268

E-mail

lee.jinwoo@kaist.ac.kr

Site

Site Url

Summary

Research Interest

Focuses on sustainable transportation infrastructure systems, particularly for electric and autonomous mobility technologies.

Education

He received his Ph.D. and M.S. degrees in Civil and Environmental Engineering from University of California Berkeley and his B.S. degree from KAIST. Before joining KAIST, he worked as a postdoctoral associate at New York University Abu Dhabi and a research assistant professor in the Department of Electrical Engineering at Hong Kong Polytechnic University.

Biography

Dr. Jinwoo Lee is an Assistant Professor in Cho Chun Shik Graduate School of Mobility at Korea Advanced Institute of Science and Technology (KAIST). His research focuses on sustainable transportation infrastructure systems, particularly for electric and autonomous mobility technologies. He received his Ph.D. and M.S. degrees in Civil and Environmental Engineering from University of California Berkeley and his B.S. degree from KAIST. Before joining KAIST, he worked as a postdoctoral associate at New York University Abu Dhabi and a research assistant professor in the Department of Electrical Engineering at Hong Kong Polytechnic University.

Publication

Journal Papers

Transportation Infrastructure Management

Pavement Management Systems (PMS)

Shon, H., Cho, C., Byon, Y. and Lee, J., 2022. Autonomous Condition Monitoring-based Pavement Management System. Automation in Construction, accepted.

Shon, H. and Lee, J., 2021. Integrating multi-scale inspection, maintenance, rehabilitation, and reconstruction decisions into system-level pavement management systems. Transportation Research Part C: Emerging Technologies, 131, p.103328.

Mizutani, D., Nakazato, Y., and Lee, J., 2020. Network-level synchronized pavement repair and work zone policies: Optimal solution and rule-based approximation. Transportation Research Part C: Emerging Technologies, 120, p.102797.

Lee, J. and Madanat, S., 2015. A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction. Transportation Research Part B: Methodological, 78, pp.106-122.

Lee, J. and Madanat, S., 2015. Jointly optimal policies for pavement maintenance, resurfacing and reconstruction. EURO Journal on Transportation and Logistics, 4(1), pp.75-95.

Lee, J. and Madanat, S., 2014. Joint optimization of pavement design, resurfacing and maintenance strategies with history-dependent deterioration models. Transportation research part B: methodological, 68, pp.141-153.

 

Environment-Friendly Highway Management

Lee, J. and Madanat, S., 2017. Optimal policies for greenhouse gas emission minimization under multiple agency budget constraints in pavement management. Transportation Research Part D: Transport and Environment, 55, pp.39-50.

Lee, J., Madanat, S. and Reger, D., 2016. Pavement systems reconstruction and resurfacing policies for minimization of life‐cycle costs under greenhouse gas emissions constraints. Transportation Research Part B: Methodological, 93, pp.618-630.

 

Disaster Management

Yun, J., Lee, J., Park, J., Chung, K., Lee, J., 2022. How to measure the network vulnerability of cities to wildfires: Cases in California. Transportation Research Record, accepted.

Papakonstantinou, I., Lee, J. and Madanat, S.M., 2019. Game theoretic approaches for highway infrastructure protection against sea level rise: Co-opetition among multiple players. Transportation Research Part B: Methodological, 123, pp.21-37.

Madanat, S.M., Papakonstantinou, I. and Lee, J., 2019. The benefits of cooperative policies for transportation network protection from sea level rise: A case study of the San Francisco Bay Area. Transport Policy, 76, pp.A1-A9.

Papakonstantinou, I., Lee, J. and Madanat, S.M., 2019. Optimal levee installation planning for highway infrastructure protection against sea level rise. Transportation Research Part D: Transport and Environment.

 

Mobility Systems

Lee, J., Shon, H., Papakonstantinou, I. and Sohn, S., 2021. Optimal fleet, battery, and charging infrastructure planning for reliable electric bus operations. Transportation Research Part D: Transport and Environment. 100, p.103066.

Ko, E., Kim, H. and Lee, J., 2021. Survey Data Analysis on Intention to Use Shared Mobility Services. Journal of Advanced Transportation, 2021.

Lee, J. and Madanat, S., 2017. Optimal design of electric vehicle public charging system in an urban network for Greenhouse Gas Emission and cost minimization. Transportation Research Part C: Emerging Technologies, 85, pp.494-508.

Griswold, J.B., Sztainer, T., Lee, J., Madanat, S. and Horvath, A., 2017. Optimizing urban bus transit network design can lead to greenhouse gas emissions reduction. Frontiers in Built Environment, 3, p.5.

 

Transportation Safety

Zeng, Q., Wen, H., Huang, H., Wang, J. and Lee, J., 2020. Analysis of crash frequency using a Bayesian underreporting count model with spatial correlation. Physica A: Statistical Mechanics and its Applications, 545, p.123754.

Lee, J., Chung, K., Papakonstantinou, I., Kang, S. and Kim, D.K., 2020. An optimal network screening method of hotspot identification for highway crashes with dynamic site length. Accident Analysis & Prevention, 135, p.105358.

Zeng, Q., Gu, W., Zhang, X., Wen, H., Lee, J. and Hao, W., 2019. Analyzing freeway crash severity using a Bayesian spatial generalized ordered logit model with conditional autoregressive priors. Accident Analysis & Prevention, 127, pp.87-95.

Lee, J., Chung, K. and Kang, S., 2016. Evaluating and addressing the effects of regression to the mean phenomenon in estimating collision frequencies on urban high collision concentration locations. Accident Analysis & Prevention, 97, pp.49-56.

Chung, K., Grembek, O., Lee, J. and Choi, K., 2013. Developing safety management tools for state departments of transportation. Transportation research record, 2364(1), pp.36-43.

 

Traffic Theories

Lee, J., Park, M. and Yeo, H., 2016. A probability model for discretionary lane changes in highways. KSCE Journal of Civil Engineering, 20(7), pp.2938-2946.

Park, M., Jang, K., Lee, J. and Yeo, H., 2015. Logistic regression model for discretionary lane changing under congested traffic. Transportmetrica A: transport science, 11(4), pp.333-344.

 

Conference Papers

Shon, H., Cho, C., Byon, Y. and Lee, J., 2022. Initial Concept of Autonomously Monitored Pavement Management Systems and Its Potential Benefits. Transportation Research Board 101st Annual Meeting. Accepted for presentation.

Shon, H. and Lee, J., 2021. Information Value in Pavement Management Systems with Surface Condition Information Collected by Autonomous Vehicles. The 14th International Conference of Eastern Asia Society for Transportation Studies (EASTS).

Shon, H. and Lee, J., 2021. Joint optimization of multi-scale decisions in budget allocation, inspection frequency, and maintenance policies for transportation infrastructure systems. Transportation Research Board 100th Annual Meeting. Accepted for presentation.

An, Y., Papakonstantinou, I., Son, S., Lee, J. Strategies to Improve the Level of Service of a Citywide Public Fast Charging Infrastructure for Electric Vehicles. Transportation Research Board (TRB) 101st Annual Meeting. Accepted for presentation.

Yun, J., Lee., J.Y., Park, J., Chung, K., Lee, J., 2021. How to Measure the Network Vulnerability of Cities to Wildfires: Cases in California. Transportation Research Record, accepted (presented at Transportation Research Board 101st Annual Meeting).

Kim, S., Lee, J., 2021. A Generalized Cost Model of Urban Air Mobility (UAM) Accounting for First and Last-Mile Access Trips: Feasibility Check with Ground-Only Mobility Services. Transportation Research Board (TRB) 101st Annual Meeting. Accepted for presentation.

Oh, S., Son, S., Papakonstantinou, I., Lee, J., 2021. Optimizing Charging Infrastructure, Fleet Size and Management, and Battery Capacity for Multi-Route Electric Bus Systems. Transportation Research Board (TRB) 101st Annual Meeting. Accepted for presentation.

Awards

  • Best Paper Award, The 86th Conference of Korean Society of Transportation, 2022
  • Best Paper Award, The 85th Conference of Korean Society of Transportation, 2021
  • Best Paper Award, The 84th Conference of Korean Society of Transportation, 2021
  • Best Paper Award, The 83rd Conference of Korean Society of Transportation, 2020
  • 2016 Outstanding Reviewer, Journal of Infrastructure Systems, 2017
  • University of California Transportation Center Dissertation Fellowship, 2014 – 2015
  • Department Fellowship, University of california at Berkeley, 2013 – 2014
  • The Army Commendation Medal, United States Department of the Army, 2008
  • Scholarship for the Top Seat of Department, KAIST, 2005 – 2010
  • Scholarship of President, Korea Student Aid Foundation, Korea, 2004 – 2010
  • Scholarship for International Olympiad Medalists, Korea Student Aid Foundation, Korea, 2004 (waived)
  • 3rd Prize, 8th International Astronomy Olympiad, Stockholm, Sweden, 2003

Research

Infrastructure Asset Management

  • Joint optimization of monitoring, inspection, maintenance, and reconstruction for large-scale infrastructure systems such as highway/bridge/railway/airport networks
  • Environmentally managed transportation asset
  • Life cycle analysis for reducing Greenhouse Gas emissions
  • Deterioration and failure modeling based on machine learning techniques
  • Pre-disaster and post-disaster infrastructure management planning
  • Game-theoretical approaches in disaster management systems

 

Teaching

CoE491, Smart Mobility for Sustainable Society (KAIST)

This course is an introductory and fusion course for the new emerging smart mobility from the perspectives of the human-society system. It deals with the trips generating from social-activity system, the mobility system, modeling AI-based methods and social issues, and future mobility technologies for sustainability. This course will be operated based on the discussion-based lectures and projects.

Keywords: Smart mobility, sustainable society, KAIST STAR(Symbiotic Transformation for AI-infused Reality) Education Course

 

GT510, Public Transportation Systems (KAIST)

This course introduces how to systemically understand public transportation systems. The scope ranges from the fundamental theories to real-world applications. Both traditional modes including buses, subways, and taxis, and emerging transit services associated with connected and autonomous vehicles (CAVs) will be discussed.

Keywords: Public transportation systems, collective transit, principal design procedure, planning, management, operations, optimization, dimensional analysis

 

GT814, Mobility Systems (KAIST)

This course will cover fundamental models in urban mobility systems. Models, analytical techniques, and solution methodologies for various topics such as shared mobility, electrified mobility, Mobility as a Service (MaaS) will be discussed.

Keywords: Urban mobility systems, flexible transit, continuous approximation methods, Connected/Autonomous/Shared/Electric (CASE) vehicles, Mobility as a Service (MaaS), Mobility on Demand (MoD), Urban Air Mobility (UAM),

 

GT814, Transportation Asset Management (KAIST)

In this course, we will discuss transportation infrastructure management systems. General infrastructure management methods are applied to gradually more complex systems, from facility-level to system-level problems. Specifically, pavement, railroad, airport, and bridge management systems will be introduced as examples, considering their unique characteristics.

Keywords: Transportation asset management, Markov Decision Processes (MDP), Condition-Based Management (CBM), Life-Cycle Analysis (LCA), Pavement Management Systems (PMS)

 

EE528, System Modelling and Optimal Control (HK PolyU)

The objective of this course is to provide students with a sound knowledge of system modeling techniques in areas of prediction and control. In addition, modern control design techniques will also be introduced.

Keywords: System models, optimal control, modeling of physical systems, linear systems, stability, controllability, observability

 

EE550, Enterprise Risk and Asset Management (HK PolyU)

This course is to: (i) allow students to appreciate how enterprise risk management and asset management contribute to business sustainability of railway operation and the required organisation; (ii) provide students with basic understanding of Enterprise Risk Management in railway industry; (iii) provide students with comprehensive understanding on asset management for railways and the concept and principles of which are also applicable to other industry sectors; (iv) enable students to acquire knowledge on the key asset management processes and techniques adopted; and (v) enable students to apply international standard and practices on asset management.

Keywords: Enterprise Risk Management (ERM), Enterprise Asset Management (EAM), Reliability Centred Maintenance (RCM)

Students

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