Explainable Mobility Intelligence Lab
Welcome to the Explainable Mobility Intelligence (EMI) Lab at Ajou University.
We are studying methodological innovations at the intersection of Generative AI, Explainable AI, and Econometrics to achieve more dynamic, disaggregated, and transparent urban transportation planning. If you have any questions or comments, please feel free to contact me at euijin@ajou.ac.kr
We are seeking smart, motivated, and friendly Undergraduate Research Interns, M.S., and Ph.D. students to join our research group!
Don't hesitate to get in touch with Prof. Kim at euijin@ajou.ac.kr
학부연구생, 석사과정, 박사과정 학생을 모집하고 있으니 위 이메일로 김의진 교수에게 직접 연락주세요.
Explainable AI for Travel Demand Forecasting
Kim, E.J., Bansal, P.*, 2024. A New Flexible and Partially Monotonic Discrete Choice Model, Transportation Research Part B: Methodologicals
Generative AI for Travel Demand Forecasting
Kim, E.J., Bansal, P.*, 2023. A Deep Generative Model for Feasible and Diverse Population Synthesis. Transportation Research Part C: Emerging Technologies
Generative Data-Fusion of Mobility data
Kim, E.J., Kim, D.K., and Sohn, K.*, 2022. Imputing Qualitative Attributes for Trip Chains Extracted from Smart Card Data Using a Conditional Generative Adversarial Network. Transportation Research Part C: Emerging Technologies
Data-driven Evaluation of Travel Behaviour
Shin, Y., Kim, D.K., and Kim, E.J.*, 2022. Activity-based TOD Typology for Seoul Transit Station Areas Using Smart-card Data. Journal of Transport Geography
Modeling Preference for Mobility-as-a-Service
Kim, E.J., Kim, Y., Jang, S.H. and Kim, D.K.*, 2021. Tourists’ Preference on the Combination of Travel Modes under Mobility-as-a-Service Environment. Transportation Research Part A: Policy and Practice