Hi, I'm Jung-Hoon Cho.
Status
Ph.D. candidate in the Department of Civil and Environmental Engineering and Laboratory for Information and Decision Systems at Massachusetts Institute of Technology (Advisor: Prof. Cathy Wu)
Research Interest
Machine Learning (Contextual Reinforcement Learning, Generalization, Transfer Learning),
Smart Transportation (Mixed Autonomy, Advisory Autonomy, Shared Mobility, Micromobility),
Sustainable Transportation and Decarbonization (Incentive Design for Eco-Driving Guidance)
News
Sep 27, 2024: Our paper (Cooperative Advisory Residual Policies for Congestion Mitigation) was accepted in ACM Journal on Autonomous Transportation Systems.
Sep 25, 2024: Our paper (Model-Based Transfer Learning for Contextual Reinforcement Learning) was accepted at NeurIPS 2024.
Sep 4, 2024: We presented our poster "Large Language Models for Travel Behavior Prediction" at the TRC-30 conference.
Sep 3, 2024: I presented our paper, "Learning-based Incentive Design for Eco-Driving Guidance," at the TRC-30 conference.
Aug 1, 2024: Our paper (Model-Based Transfer Learning for Contextual Reinforcement Learning) was accepted at EWRL17.
May 26-29, 2024: Attended 2024 IEEE ITS WiE/YP Workshop and Research Forum.
Apr 2, 2024: Passed General Exam at MIT CEE.
Mar 28, 2024: Our paper (Expert with Clustering: Hierarchical Online Preference Learning Framework) was accepted at L4DC 2024.
Feb 29, 2024: Our paper (Incentive Design for Eco-driving in Urban Transportation Networks) was accepted at ECC 24.
Feb 26, 2024: Poster presentation at MIT CEE research day.
Feb 23, 2024: Received the fellowship to join the 2024 IEEE ITS WiE/YP Workshop and Research Forum.
Jan 4, 2024: Gave a talk (Learning for Traffic Flow Optimization) at the University of Seoul.
Feb 14, 2023: Poster presentation at MIT CEE research day.
August 19, 2022: Happy to join Wu Lab at MIT!
May 2022: Honor to receive a scholarship from the Kwanjeong Educational Foundation.
April 30, 2022: Our paper (Multi-scale Causality Analysis between COVID-19 Cases and Mobility Using Ensemble Empirical Mode Decomposition and Causal Decomposition) was published in Physica A.
Selected work
Cho, J.-H., Jayawardana, V., Li, S. & Wu, C.* (2024). Model-Based Transfer Learning for Contextual Reinforcement Learning. Advances in Neural Information Processing Systems (NeurIPS), 2024. https://arxiv.org/abs/2408.04498.
Cho, J.-H., Li, S., Kim, J., & Wu, C.* (2023). Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy. https://arxiv.org/abs/2312.09436.
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. https://doi.org/10.1177/03611981211012003.
Get in touch at jhooncho [at] mit [dot] edu