Dr. Inhi Kim
Dr. Inhi Kim
Dr. Kim received his Ph.D. from the Department of Civil Engineering at the University of Queensland, Australia, in 2014. He joined the Department of Civil Engineering, Monash University, Melbourne, Australia as a lecturer (Assistant professor) in 2015 and a senior lecturer (Associate professor) in 2019. Dr. Kim moved back to his own country and had a new position as an associate professor at Kongju National University in 2019. Inhi finally settled at Cho Chun Shik Graduate School, KAIST, in 2023.
Before joining academia, Inhi worked in the German transport software company PTV Group as a transport engineer and planner. He gained 5-year experience whilst based in Australia, Singapore, Germany, the United Arab Emirates, and Korea. He was closely involved with transport and traffic planning and modeling, evaluation, and performance measurement of transport programs and projects as a practitioner, researcher, and trainer.
Dr. Kim has particular interests and skills in the areas of deep learning, visualization, demand forecasting, strategic planning, traffic signal operation, public transportation planning, and safety in conjunction with the integration of traffic simulation and driving simulator and evaluation of connected cars in safety and efficiency.
Please visit my research homepage: http://inhi.kim/
And transport group: http://kaistmobilitygroup.com/
Qualifications
- Ph.D, Civil Engineering, University of Queensland., 2014
Professional Association:
Standing Committee on Highway/Rail Grade Crossings TRB – AHB60
Program committee of ANT
Korean Society of Transportation
The Korean Institute of Intelligent Transport Systems
Korean Academy of Scientists and Engineers in Australasia
Research Projects
Past projects
Evaluation traffic demand management policies in a dynamic agent based activity scheduling model
Signal control through reinforcement learning
External research funding
Vissim and Unity Integration Modelling Study by MainRoads, WA 2019; AUD 24,000; Lead CI
Passenger Flow Evaluation Study by Bombardier Australia 2019; AUD 36,000; CI
Smart mobility by CCDI, China 2019; 350,000 RMB (AUD 73,000); Lead CI
Localization and environmental awareness for autonomous vehicles, Data 61; 2018-2021; AUD 129,787; Lead CI
Research on Collaborative Model of Green Travel in Intelligent City Integration platform by Jiangsu province, China 2017-2019; 4million RMB (AUD 760,000); Lead CI
The traffic operational reliability analysis and optimization design of connection lines between motorways and urban roads by National Natural Science Foundation of China 2016-2020; 620,000 RMB (AUD 117,000) CI
Research on characteristics of driving rage and intervention method in China funded by Traffic Management Research Institute of the Ministry of Public Security in Wuxi, China 2016-2017; 30,000 RMB (AUD 5,700); Lead CI
Internal research funding
Dynamic traffic assignment model on Domino with road pricing, 2018 Engineering Seed Funding Scheme Monash University, AUD 25,000. Lead CI
Mitigating vehicle crash and emission using Intelligent traffic system, 2015 Engineering Seed Funding Scheme Monash University, AUD 25,000. Lead CI
Supervision
PHD
Taeho Oh
Activity based modelling
2020 to Present
Dong Xiao
Travel Patterns Identification From Longitudinal Perspectives by Using Mobile Phone Data
2019 to 2024
Wenhua Jia
Railway station passenger flow short term estimation.
2017 to 2022
Chunlian Wu
Signal control through reinforcement learning
2018 to 2023
Bo Wang
Traffic prediction using deep learning
2018 to 2023
Tianqi Gu
E-Bike and public-shard bike’s mobility, feasibility and safety.
2016 to 2019
Xinyuan Chen
Optimal setting of rail based park and ride scheme with feeder bus services.
2015 to 2019
Wentao Jing
Evaluation traffic demand management policies in a dynamic agent based activity scheduling model.
2014 to 2018
Xiaoying Cao
Modelling forced lane change execution in heterogeneous traffic on arterial road.
2014 to 2017