News
| Jan 2026 | We presented our poster "Structure Detection for Contextual Reinforcement Learning" at AAAI 2026.
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| Jan 2026 | Our paper on Formalizing Task-Space Complexity for Zero-shot Generalization was accepted at L4DC 2026.
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| Jan 2026 | Our paper on Route Recommendations for Traffic Management was accepted at ACC 2026.
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| Oct 2025 | Our paper on Eco-driving Incentive Mechanisms was accepted in IEEE TCNS.
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| Oct 2025 | Our paper on Temporal Transfer Learning for Advisory Autonomy was accepted in IEEE T-RO.
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| Aug 2025 | I gave a talk at Cornell IDS Lab on Model-Based Transfer Learning for Contextual Dynamical Systems.
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| Jun 2025 | Our paper on Nah Bandit for User Non-compliance was accepted in IEEE TCNS.
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| Jan 2025 | Our paper on RL for Robust Advisories was accepted in IEEE T-ITS.
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| Dec 2024 | We presented our poster on Model-Based Transfer Learning for Contextual RL at NeurIPS 2024.
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| Nov 2024 | Our paper featured by MIT News and SciTechDaily!
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| Apr 2024 | Passed General Exam at MIT CEE. |
| Mar 2024 | Our paper on Expert with Clustering was accepted at L4DC 2024.
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| Feb 2024 | Our paper on Incentive Design for Eco-driving was accepted at ECC 2024.
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| Feb 2024 | Received the fellowship to join the 2024 IEEE ITS WiE/YP Workshop and Research Forum. See you in Seoul!
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| Jan 2024 | I gave a talk at University of Seoul on Learning for Traffic Flow Optimization.
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| Aug 2022 | Joined Wu Lab at MIT!
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| May 2022 | Received Kwanjeong Scholarship from the Kwanjeong Educational Foundation. |
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Research
My research lies at the intersection of machine learning and smart transportation. I develop reinforcement learning (RL) methods for complex transportation problems where human behavior and environmental variability make reliable decision-making challenging. Applications include shared autonomy, advisory autonomy, eco-driving, mixed-autonomy traffic, and agentic simulation.
Representative papers are highlighted.
Papers in reverse chronological order. († equal contribution, * corresponding author)
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Machine Learning
Transportation
Control / Robotics
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AGORA: Can Deliberation and Governance Gates Absorb Participation Bias in Transit Planning?
Jung-Hoon Cho, Cathy Wu*
Under review, 2026
Machine Learning
Transportation
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Formalizing and Estimating Task-Space Complexity for Zero-shot Generalization
Jung-Hoon Cho, Heling Zhang, Siqi Du, Roy Dong, Cathy Wu*
Under review, 2026
[L4DC 2026] Learning for Dynamics and Control Conference
(Poster)
Machine Learning
Control / Robotics
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Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy
Jung-Hoon Cho, Sirui Li, Jeongyun Kim, Cathy Wu*
[IEEE T-RO 2026] IEEE Transactions on Robotics
paper
[ICRA 2026] IEEE International Conference on Robotics & Automation
Machine Learning
Transportation
Control / Robotics
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Route Recommendations for Traffic Management Under Learned Partial Driver Compliance
Heeseung Bang†, Jung-Hoon Cho†, Cathy Wu, Andreas A. Malikopoulos
[ACC 2026] American Control Conference
(Oral)
arXiv
Transportation
Control / Robotics
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Structure Detection for Contextual Reinforcement Learning
Tianyue Zhou†, Jung-Hoon Cho†, Cathy Wu*
[AAAI 2026] AAAI Conference on Artificial Intelligence
(Poster)
(acceptance rate: 17.6%)
arXiv / webpage
Machine Learning
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Large Language Models for Travel Behavior Prediction
Baichuan Mo, Hanyoung Xu*, Ruoyun Ma, Jung-Hoon Cho, Dingyi Zhuang, Xiaotong Guo, Jinhua Zhao
Under review, 2026
[TRC-30 2024] Conference in Emerging Technologies in Transportation Systems
(Poster)
abstract
Machine Learning
Transportation
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Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation
M. Umar B. Niazi, Jung-Hoon Cho, Munther A. Dahleh, Roy Dong, Cathy Wu*
[IEEE TCNS 2026] IEEE Transactions on Control of Network Systems
arXiv
[ECC 2024] European Control Conference
(Oral)
arXiv
Transportation
Control / Robotics
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Learning-Based Incentive Design for Promoting Eco-Driving in Urban Transportation
Jung-Hoon Cho, M. Umar B. Niazi, Siqi Du, Roy Dong, Cathy Wu*
In preparation, 2025
abstract
[TRC-30 2024] Conference in Emerging Technologies in Transportation Systems
(Oral)
abstract
Machine Learning
Transportation
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Nah Bandit for Modeling User Non-compliance in Recommendation Systems
Tianyue Zhou, Jung-Hoon Cho, Cathy Wu*
[IEEE TCNS 2025] IEEE Transactions on Control of Network Systems
paper / webpage
Machine Learning
Control / Robotics
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Reinforcement Learning for Robust Advisories under Driving Compliance Errors
Jeongyun Kim, Jung-Hoon Cho, Cathy Wu*
[IEEE T-ITS 2025] IEEE Transactions on Intelligent Transportation Systems
paper
Machine Learning
Transportation
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Model-Based Transfer Learning for Contextual Reinforcement Learning
Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu*
[NeurIPS 2024] Conference on Neural Information Processing Systems
(Poster)
(acceptance rate: 25.8%)
arXiv / webpage
Media:
MIT News | SciTechDaily
Machine Learning
Transportation
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Cooperative Advisory Residual Policies for Congestion Mitigation
Aamir Hasan, Neeloy Chakraborty, Haonan Chen, Jung-Hoon Cho, Cathy Wu, Katherine Driggs-Campbell
[ACM JATS 2024] ACM Journal on Autonomous Transportation Systems
paper
[IEEE ITSC 2023] IEEE International Conference on Intelligent Transportation Systems
(Oral)
paper
Machine Learning
Transportation
Control / Robotics
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Expert with Clustering: Hierarchical Online Preference Learning Framework
Tianyue Zhou, Jung-Hoon Cho, Babak Rahimi Ardabili, Hamed Tabkhi, Cathy Wu
[L4DC 2024] Learning for Dynamics and Control Conference
(Poster)
arXiv
Machine Learning
Transportation
Control / Robotics
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Multi-scale Causality Analysis between COVID-19 Cases and Mobility Level Using Ensemble Empirical Mode Decomposition and Causal Decomposition
Jung-Hoon Cho, Dong-Kyu Kim, Eui-Jin Kim*
[Physica A 2022] Physica A: Statistical Mechanics and its Applications
paper
Transportation
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Developing Variable Speed Limit Control and Ramp Metering Strategy for Freeways Using Deep Reinforcement Learning
Jung-Hoon Cho
[M.S. Thesis 2022] Seoul National University
Machine Learning
Transportation
Control / Robotics
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A Comparative Analysis of Usage Patterns of Bike-sharing and E-scooter-sharing in Seoul
Jung-Hoon Cho, Seung Woo Ham, Eui-Jin Kim, Dong-Kyu Kim*
[TRBAM 2022] Transportation Research Board 101st Annual Meeting
(Poster)
Transportation
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Efficiency Comparison of Public Bike-sharing Repositioning Strategies Based on Predicted Demand Patterns
Jung-Hoon Cho, Young-Hyun Seo, Dong-Kyu Kim*
[TRR 2021] Transportation Research Record
paper
[B.S. Thesis 2020] Seoul National University
Transportation
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Enhancing the Accuracy of Peak Hourly Demand in Bike-Sharing Systems Using a Graph Convolutional Network with Public Transit Usage Data
Jung-Hoon Cho, Seung Woo Ham, Dong-Kyu Kim*
[TRR 2021] Transportation Research Record
paper
[TRBAM 2021] Transportation Research Board 100th Annual Meeting
(Poster)
Machine Learning
Transportation
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Spatiotemporal Demand Prediction Model for E-scooter Sharing Services with Latent Feature and Deep Learning
Seung Woo Ham, Jung-Hoon Cho, Sangwoo Park, Dong-Kyu Kim*
[TRR 2021] Transportation Research Record
paper
Machine Learning
Transportation
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Education
Massachusetts Institute of Technology
Ph.D. in Civil and Environmental Engineering, Sep 2022 - present
Advisor: Prof. Cathy Wu
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Cambridge, MA |
Seoul National University
M.S. in Civil and Environmental Engineering, Mar 2020 - Feb 2022
Advisor: Prof. Dong-Kyu Kim and Prof. Seung-Young Kho
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Seoul, Korea |
Seoul National University
B.S. in Civil and Environmental Engineering, Mar 2014 - Feb 2020
Advisor: Prof. Dong-Kyu Kim
Cum laude, Best Thesis Award (2nd place) |
Seoul, Korea |
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Honors & Awards
| Kwanjeong Scholarship, Kwanjeong Educational Foundation | 2022 - Present |
| Fellowship Program for Promoting Diversity and Leadership in ITS, IEEE ITSS | 2024 |
| Speedwell Foundation and the Robert E. Thurber Fellowship, MIT CEE | 2022 - 2023 |
| KOTAA TRB Annual Meeting Travel Grant, KOTAA | 2022, 2021 |
| Best B.S. Thesis Paper Award, SNU CEE | 2019 |
| Best Portfolio Award, SNU CEE | 2019 |
| Best Undergraduate Paper Award, Korean Institute of Intelligent Transportation Systems | 2019 |
| Academic Excellence Award (GPA 4.30/4.30), SNU CEE | 2018 |
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Invited Talks
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Cornell IDS Lab
Seminar: "Model-Based Transfer Learning for Contextual Dynamical System"
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Aug 2025 |
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MIT LIDS Autonomy Tea Talk
Seminar: "Model-Based Transfer Learning for Contextual Reinforcement Learning"
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Nov 2024 |
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University of Seoul
Seminar: "Learning for Traffic Flow Optimization"
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Jan 2024 |
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KOSEN
Seminar: "Studying in a U.S. Graduate School: Preparing for a New Start"
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Jun 2023 |
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Unjung High School
Seminar: "Smart Mobility System Using Machine Learning and Data Science"
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Jul 2022, Jul 2021 |
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Teaching
| 1.041/1.200: Transportation: Foundations and Methods – Teaching Assistant, MIT |
Spring 2026 |
| Introduction to Traffic Operation – Teaching Assistant, SNU |
Spring 2021, 2020 |
| Public Transportation Engineering – Teaching Assistant, SNU |
Spring 2021 |
| Integrated Design of Civil Engineering Systems – Teaching Assistant, SNU |
Fall 2020 |
| Traffic Engineering and Laboratory – Teaching Assistant, SNU |
Fall 2020 |
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Academic Service
Journal Reviewer:
Transportation: Transportation Research Part C: Emerging Technologies, IEEE Transactions on Intelligent Transportation Systems (T-ITS), Transportation Research Records (TRR), Transportation, Transport Policy, Data Science for Transportation, Journal of Korean Society of Transportation, Discover Cities.
Others: Scientific Report, Journal of Big Data, Physica A, IEEE Transactions on Control Systems Technology (TCST), Knowledge and Information Systems.
Conference Reviewer:
AI/ML: AAAI (2026), RLC (2025), ICML (2025), AISTATS (2025), NeurIPS (2025, 2024).
Transportation: TRBAM (2026, 2025), ITS WC (2026, 2025, 2024), IEEE ITSC (2026, 2025, 2024), IEEE IV (2026, 2024).
Control/Robotics: ACC (2026, 2025), ECC (2024), ICRA (2026, 2025).
Other:
Mentor for MIT-UF-NEU Joint Summer Research Camp (2026 - Present), Mentor for MIT CEE Graduate Application Assistance Program (GAAP) (2024 - Present), Mentor for MIT CEE Peer Mentorship Program (2024 - Present), Mentor for MIT CEE Mini-UROP (2026), Organizing Committee and Mentor for ITSS Incubator (2024), Organizing Committee for MIT LIDS & Stats Tea Talks (2023 - 2024).
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Students Mentored
| Undergraduate Students |
George Cao (MIT UROP & 6.7920), Andrew Zheng (MIT 6.7920), Ruth Lu (MIT UROP), Anniston Pierce (MIT Mini UROP), Tan Le (MIT Mini UROP), Stephen Andrews (MIT UROP), Tianyue Zhou (ShanghaiTech, currently MIT PhD student), Sanjula Jayawardana (ITSS Incubator), Rajeev Datta (Caltech, currently Cornell PhD student) |
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Teach For Korea, Seoul, Korea
| Planning and Operation Manager (HQ) |
2019 - 2020 |
| Principal Teacher (Seongbuk School) |
2016 |
| Head of Financial Administration (HQ) |
2015 - 2016 |
| Led classes in Mathematics, Physics, and Chemistry (13 months, 550+ hours) (Seongbuk School) |
2015 - 2016 |
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Republic of Korea Army, Yeoncheon, Korea
| Mandatory Military Service |
2016 - 2018 |
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