Papers under review
Papers under review
Niazi, M., Cho, J.-H., Dahleh, M., Dong, R., & Wu, C.* (2024). Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation. Under review.
Zhou, T., Cho, J.-H., & Wu, C.* (2024). Nah Bandit for Modeling User Non-compliance in Recommendation Systems. In revision. [preprint]
Cho, J.-H., Li, S., Kim, J., & Wu, C.* (2024). Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy. In revision. [preprint]
Kim, J., Cho, J.-H., & Wu, C.* (2025). Learning for Robust Advisory Autonomy under Execution Errors. IEEE Transactions on Intelligent Transportation Systems (T-ITS). [link]
Hasan, A., Chakraborty, N., Chen, H., Cho, J.-H., Wu, C. & Driggs-Campbell, K. (2024). Cooperative Advisory Residual Policies for Congestion Mitigation. ACM Journal on Autonomous Transportation Systems. [link]
Cho, J.-H., Kim, D.-K., & Kim, E.-J.* (2022). Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition. Physica A: Statistical Mechanics and its Applications. [link]
Cho, J.-H., Seo, Y.-H., & Kim, D.-K.* (2021). Efficiency Comparison of Public Bike-sharing Repositioning Strategies Based on Predicted Demand Patterns. Transportation Research Record: Journal of the Transportation Research Board. [link]
Cho, J.-H., Ham, S. W., & Kim, D.-K.* (2021). Enhancing the Accuracy of Peak Hourly Demand in Bike-Sharing Systems Using a Graph Convolutional Network with Public Transit Usage Data. Transportation Research Record: Journal of the Transportation Research Board. [link]
Ham, S. W., Cho, J.-H., Park, S.-W., & Kim, D.-K.* (2021). Spatiotemporal Demand Prediction Model for E-scooter Sharing Services with Latent Feature and Deep Learning. Transportation Research Record: Journal of the Transportation Research Board. [link]
Cho, J.-H., Jayawardana, V., Li, S. & Wu, C.* (2024, Dec 9-15). Model-Based Transfer Learning for Contextual Reinforcement Learning [Poster presentation]. Advances in Neural Information Processing Systems (NeurIPS), Vancouver, Canada. [preprint] [webpage] [MIT News]
Cho, J.-H., Niazi, M., Du, S., Zhou, T., Dong, R., & Wu, C.* (2024, Sep 2-4). Learning-based Incentive Design for Eco-Driving Guidance [Oral presentation]. Conference in Emerging Technologies in Transportation Systems (TRC-30), Crete, Greece.
Mo, B., Xu, H., Cho, J.-H., Zhuang, D., Ma, R., Guo, X., & Zhao, J.* (2024, Sep 2-4). Large Language Models for Travel Behavior Prediction [Poster presentation]. Conference in Emerging Technologies in Transportation Systems (TRC-30), Crete, Greece.
Zhou, T., Cho, J.-H., Ardabili, B. R., Tabkhi, H., & Wu, C.* (2024, July 15-17). Expert with Clustering: Hierarchical Online Preference Learning Framework. 6th Annual Learning for Dynamics & Control Conference, Oxford, UK. [link]
Niazi, M., Cho, J.-H., Dahleh, M., Dong, R., & Wu, C.* (2024, June 25-28). Incentive Design for Eco-driving in Urban Transportation Networks. European Control Conference, Stockholm, Sweden.
Hasan, A., Chakraborty, N., Chen, H., Cho, J.-H., Wu, C. & Driggs-Campbell, K. (2023, Septem- ber 24-28), PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systems. 26th IEEE International Conference on Intelligent Transportation Systems, Bilbao, Spain. [link]
Cho, J.-H., Ham, S. W., Kim, E.-J., & Kim, D.-K.* (2022, January 9–13). A Comparative Analysis of Usage Patterns of Bike-sharing and E-scooter-sharing in Seoul [Poster presentation]. Transportation Research Board 101st Annual Meeting, Washington DC, United States.
Cho, J.-H., Lee, E. H., Kho, S.-Y., & Kim, D.-K.* (2021, November 11–12). Developing Variable Speed Limit Control and Ramp Metering Strategy for Freeways Using Deep Reinforcement Learning (Korean) [Oral presentation]. 85th Conference on the Korean Society of Transportation, Jeju, Korea.
Cho, J.-H., & Kim, D.-K.* (2021, October 21–22). Reinforcement Learning based Variable Speed Limit Control Strategy on Each Lane to Prevent Accident caused by the reduction of highway lanes (Korean) [Oral presentation]. 2021 Fall Conference on the Korea Institute of Intelligent Transport Systems, Jeju, Korea.
Ham, S. W., Cho, J.-H., & Kim, D.-K.* (2021, April 22–23). Establishing Micro-Mobility Demand Aggregation Methodology Considering Interregional Relationship (Korean) [Oral presentation]. 2021 Spring Conference on the Korea Institute of Intelligent Transport Systems, Gangneung, Korea.
Cho, J.-H., Ham, S. W., & Kim, D.-K.* (2021, January 24–28). Enhancing the Accuracy of Peak Hourly Demand in Bike-Sharing Systems Using a Graph Convolutional Network with Public Transit Usage Data [Poster presentation]. Transportation Research Board 100th Annual Meeting, Washington DC, United States. [Link]
Cho, J.-H., Ham, S. W., & Kim, D.-K.* (2020, November 19–20). A Comparison study on Micro-mobility Usage Pattern: focusing on Bike-sharing service and E-Scooter share service in Seoul, Korea (Korean) [Oral presentation]. 2020 Fall Conference on the Korea Institute of Intelligent Transport Systems, Jeju, Korea.
Scientific Report (2024), Journal of Big Data (2024), Transportation (2024), Journal of Korean Society of Transportation (2023)
AISTATS (2025), ACC (2025), ICRA (2025), TRBAM (2025), NeurIPS (2024), ITS WC (2024), IEEE ITSC (2024), IEEE IV (2024), ECC (2023)
Three students (MIT CEE GAAP) | 2024 – present
Sanjula Jayawardana (ITSS Incubator) | 2024 – present
Tianyue Zhou (ShanghaiTech, MIT) | 2023 – present
Rajeev Datta (CalTech, MIT) | 2023
Organizing Committee for ITSS Incubator | 2024 – present
Organizing Committee for MIT LIDS & Stats Tea Talks | 2023 – 2024