Jung-Hoon Cho

I am a Ph.D. candidate in the Department of Civil and Environmental Engineering and Laboratory for Information and Decision Systems (LIDS) at Massachusetts Institute of Technology (MIT), advised by Prof. Cathy Wu.

My research lies at the intersection of machine learning and smart transportation. I develop contextual reinforcement learning methods for complex transportation problems where human behavior and environmental variability make reliable decision-making challenging. Applications include shared autonomy, advisory autonomy, eco-driving, incentive design, mixed-autonomy traffic, and agentic modeling.

I received my M.S. and B.S. in Civil and Environmental Engineering from Seoul National University, where I was advised by Prof. Dong-Kyu Kim and Prof. Seung-Young Kho.

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News
Jan 2026We presented our poster "Structure Detection for Contextual Reinforcement Learning" at AAAI 2026.
Jan 2026Our paper on Formalizing Task-Space Complexity for Zero-shot Generalization was accepted at L4DC 2026.
Jan 2026Our paper on Route Recommendations for Traffic Management was accepted at ACC 2026.
Oct 2025Our paper on Eco-driving Incentive Mechanisms was accepted in IEEE TCNS.
Oct 2025Our paper on Temporal Transfer Learning for Advisory Autonomy was accepted in IEEE T-RO.
Aug 2025I gave a talk at Cornell IDS Lab on Model-Based Transfer Learning for Contextual Dynamical Systems.
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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)

Filter: All Selected
Area: All Machine Learning Transportation Control / Robotics
AGORA: Can Deliberation and Governance Gates Absorb Participation Bias in Transit Planning?
AGORA: Can Deliberation and Governance Gates Absorb Participation Bias in Transit Planning?
Jung-Hoon Cho, Cathy Wu*
Under review, 2026
Machine Learning Transportation
Formalizing and Estimating Task-Space Complexity for Zero-shot Generalization
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
Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy
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
Route Recommendations for Traffic Management Under Learned Partial Driver Compliance
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
Structure Detection for Contextual Reinforcement Learning
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
Large Language Models for Travel Behavior Prediction
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
Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation
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
Learning-Based Incentive Design for Promoting Eco-Driving in Urban Transportation
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
Nah Bandit for Modeling User Non-compliance in Recommendation Systems
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
Reinforcement Learning for Robust Advisories under Driving Compliance Errors
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
Model-Based Transfer Learning for Contextual Reinforcement Learning
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
Cooperative Advisory Residual Policies for Congestion Mitigation
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
Expert with Clustering: Hierarchical Online Preference Learning Framework
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
Multi-scale Causality Analysis between COVID-19 Cases and Mobility Level Using Ensemble Empirical Mode Decomposition and Causal Decomposition
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
Developing Variable Speed Limit Control and Ramp Metering Strategy for Freeways Using Deep Reinforcement Learning
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
A Comparative Analysis of Usage Patterns of Bike-sharing and E-scooter-sharing in Seoul
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
Efficiency Comparison of Public Bike-sharing Repositioning Strategies Based on Predicted Demand Patterns
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
Enhancing the Accuracy of Peak Hourly Demand in Bike-Sharing Systems Using a Graph Convolutional Network with Public Transit Usage Data
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
Spatiotemporal Demand Prediction Model for E-scooter Sharing Services with Latent Feature and Deep Learning
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
Education
Massachusetts Institute of Technology
Ph.D. in Civil and Environmental Engineering, Sep 2022 - present
Advisor: Prof. Cathy Wu
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
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
Experience
Massachusetts Institute of Technology
Graduate Research Assistant (Laboratory for Information & Decision Systems (LIDS))
Aug 2022 - present
PI: Prof. Cathy Wu
MA, USA
Seoul National University
Researcher (Institute of Engineering Research)
Apr 2022 - Jul 2022
PI: Prof. Dong-Kyu Kim
Seoul, Korea
Seoul National University
Graduate Researcher (Transportation Research Laboratory)
Feb 2020 - Feb 2022
PI: Prof. Dong-Kyu Kim and Prof. Seung-Young Kho
Seoul, Korea
VCNC Inc.
Value Innovator (Intern) (TADA Business Development Team)
Jun 2019 - Aug 2019
Seoul, Korea
Honors & Awards
Kwanjeong Scholarship, Kwanjeong Educational Foundation2022 - Present
Fellowship Program for Promoting Diversity and Leadership in ITS, IEEE ITSS2024
Speedwell Foundation and the Robert E. Thurber Fellowship, MIT CEE2022 - 2023
KOTAA TRB Annual Meeting Travel Grant, KOTAA2022, 2021
Best B.S. Thesis Paper Award, SNU CEE2019
Best Portfolio Award, SNU CEE2019
Best Undergraduate Paper Award, Korean Institute of Intelligent Transportation Systems2019
Academic Excellence Award (GPA 4.30/4.30), SNU CEE2018
Invited Talks
Cornell IDS Lab Seminar: "Model-Based Transfer Learning for Contextual Dynamical System" Aug 2025
MIT LIDS Autonomy Tea Talk Seminar: "Model-Based Transfer Learning for Contextual Reinforcement Learning" Nov 2024
University of Seoul Seminar: "Learning for Traffic Flow Optimization" Jan 2024
KOSEN Seminar: "Studying in a U.S. Graduate School: Preparing for a New Start" Jun 2023
Unjung High School Seminar: "Smart Mobility System Using Machine Learning and Data Science" Jul 2022, Jul 2021
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
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).

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)
Volunteering & Service
Teach For Korea 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
Republic of Korea Army Republic of Korea Army, Yeoncheon, Korea
Mandatory Military Service 2016 - 2018

Design adapted from Dingyi Zhuang, Vindula Jayawardana, and Jon Barron. Last updated: March 2026.