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Heye Huang 

Full-time FacultyResearch Field > Intelligent Mobility TechnologyResearch Field > Sustainable Mobility Technology

Office

F337

Tel

1765

E-mail

heye.huang@kaist.ac.kr

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Summary

Research Interest

• Safe and trustworthy autonomy
• Safe embodied intelligence
• Generative AI and world models
• Foundation models and agents
• Autonomous mobility systems

Education

  • Ph.D. in Mechanical Engineering, Tsinghua University, 2023.
  • Visiting Scholar in Cognitive Robotics, Delft University of Technology, 2022.
  • B.E. in Transport Equipment & Control Engineering, Central South University, 2018.

Academic Experience

  • Apr. 2026 – Present, Assistant Professor, Cho Chun Shik Graduate School of Mobility, KAIST
  • Sep. 2025 – Apr. 2026, Postdoctoral Associate, SMART Center, MIT
  • Aug. 2023 – Aug. 2025, Research Associate, UW-Madison

Biography

Dr. Heye Huang is an Assistant Professor at the Cho Chun Shik Graduate School of Mobility, KAIST. Before joining KAIST, she was a postdoctoral associate at the MIT SMART Center and also worked as a research associate at the University of Wisconsin-Madison. Dr. Huang received the Ph.D. degree from the School of Vehicle and Mobility, Tsinghua University, she was a visiting scholar at the Department of Cognitive Robotics, Delft University of Technology, and gained additional research experience at UC Berkeley and the TUM. Her research centers on developing generative models and human-centered AI to enable safe, reliable, and trustworthy autonomy in safety-critical systems.

Publication

Section A – Selected Publications

[1]      H. Huang, Y. Yang, M. Fan, H. Wang, X. Zhao, J. Wang. “CogDrive: Cognition-Driven Multimodal Prediction-Planning Fusion for Safe Autonomy”. Communication in transportation research, 2026. (Q1, Impact Factor: 14.5)
[2]      H. Huang, J. Liu, S. Zhao, B. Li, J. Wang. “LEAD: Learning-Enhanced Adaptive Decision-Making for Autonomous Driving in Dynamic Environments”. IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2025. (Q1, Impact Factor: 8.4)
[3]      H. Huang, H. Cheng, Z. Zhou, Z. Wang, Q. Liu, X. Li. “REACT: Runtime-Enabled Active Collision-avoidance Technique for Autonomous Driving.” Advanced Engineering Informatics, accepted. (Q1, IF: 9.9)
[4]      H. Huang, Z. Li, H. Cheng, J. Jiang, X. Li, A. Zgonnikov. “Understanding Driver Cognition and Decision-Making Behaviors in High-Risk Scenarios: A Drift Diffusion Perspective”. Accident Analysis & Prevention (AAP), 2025. (Q1, Impact Factor: 6.2)
[5]      H. Huang, Y. Liu, J. Liu, Q. Yang, J. Wang, D. Abbink, A. Zgonnikov. “General Optimal Trajectory Planning: Enabling Autonomous Vehicles with the Principle of Least Action”. Engineering, 2024. (Q1, Impact Factor: 11.6)
[6]      H. Huang, J. Liu, Y. Yang, J. Wang. “Risk Generation and Identification of Driver–Vehicle–Road Microtraffic System”. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, 2022. (Q2)  (Best Paper Award)
[7]      H. Huang, J. Liu, X. Zheng, W. Liu, J. Wang. “Probabilistic Situation Assessment for Intelligent Vehicles with Uncertain Trajectory Distribution”. Transportation Research Record, 2021. (Q3)
[8]      H. Huang, X. Zheng, Y. Yang, J. Liu, W. Liu, J. Wang. “An Integrated Architecture for Intelligence Evaluation of Automated Vehicles”. AAP, 2020. (Q1, IF: 6.2) (Best Paper Award)
[9]      H. Huang, J. Wang, C. Fei, X. Zheng, Y. Yang, J. Liu, X. Wu, Q. Xu. “A Probabilistic Risk Assessment Framework Considering Lane-Changing Behavior Interaction”. Science China Information Sciences, 2020. (Q1, Impact Factor: 7.6)
[10]   J. Wang#, H. Huang#, K. Li, J. Li. “Towards The Unified Principles for Level 5 Autonomous Vehicles”. Engineering, 2021. (Q1, Impact Factor: 11.6) (Journal Cover Paper)
[11]   J. Wang#, H. Huang#, Y. Li, H. Zhou, J. Liu, Q. Xu. “Driving Risk Assessment Based on Naturalistic Driving Study and Driver Attitude Questionnaire Analysis”. Accident Analysis & Prevention, 2020. (Q1, Impact Factor: 6.2)
[12]   Q. Liu, H. Huang*, S. Zhao, L. Shi, S. Ahn, X. Li. “RiskNet: Interaction-Aware Risk Forecasting for Autonomous Driving in Long-Tail Scenarios”. Transportation Research Part E: Logistics and Transportation Review (TR-E) , accepted. (Q1, Impact Factor: 8.8)
[13]   P. Zhang, H. Huang*, H. Zhou, H. Shi, K. Long, X. Li. “Online Adaptive Platoon Control for Connected and Automated Vehicles via Physics Enhanced Residual Learning”. Transportation Research Part C: Emerging Technologies, 2025. (Q1, Impact Factor: 7.9)
[14]   Z. Zhou, H. Huang*, B. Li, S. Zhao, Y. Mu, J. Wang. “SafeDrive: Knowledge-and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models”. Accident Analysis & Prevention, 2025. (Q1, Impact Factor: 6.2)
[15]   Y. Yang, S. Xu, X. Yan, J. Jiang, J. Wang, H. Huang*. “CSDO: Enhancing Efficiency and Success in Large-Scale Multi-Vehicle Trajectory Planning”. IEEE Robotics and Automation Letters (RA-L), 2024. (Q1, IF: 5.3)
Section B – Papers Under Review:
[1]     W. Chen#, H. Huang#, K. Ma, H. Li, S. Liang, H. Zhou, X. Li. “Unveiling Uniform Shifted Power Law in Stochastic Human and Autonomous Driving Behavior”. Preprint, 2025.
[2]      H. Huang, Y. Yang, W. Chen, T. Chen, X. Li, S. Chen. “SMART: Scalable Multi-Agent Reasoning and Trajectory Planning in Dense Environments”. Transportation Research Part C: Emerging Technologies, under revision, 2025. (Q1, Impact Factor: 7.6)
[3]      Y. Wang, H. Huang*, Z. Xu, K. Sun, B. Guo, J. Zhao. “Learning from Risk: LLM-Guided Generation of Safety-Critical Scenarios with Prior Knowledge”. Transportation Research Part E: Logistics and Transportation Review, under review, 2025. (Q1, Impact Factor: 8.8)
[4]      D. Chen, H. Huang*, T. Chen, Z. Li, Y. Li, Y. Xu, S. Chen. “RESPOND: Risk-Enhanced Structured Pattern for LLM-driven Online Node-level Decision-making”. Communication in transportation research, under review, 2026. (Q1, Impact Factor: 14.5)
Section C- Selected International Conferences:
[1]      H. Huang, X. Zheng, Y. Liu, S. Zhao, Y. Wang, J. Wang. “Intelligent Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Scenarios”.  IEEE International Conference on Digital Society and Intelligent Systems (DSInS), 2023. (Best Paper Award)
[2]      H. Huang, Y. Li, X. Zheng, J. Wang, Q. Xu, S. Zheng. “Objective and Subjective Analysis to Quantify Influence Factors of Driving Risk”. IEEE ITSC, 2019.
[3]      H. Huang, Y. Liu, X. Zheng. “Analysis of the Influence of Community Opening on Road Capacity”. In Intelligent Transport Systems World Congress (ITSWC), 2019.
[4]      H. Huang, J. Wang, et al. “Path Planning for Vehicle Obstacle Avoidance Based on Collaborative Perception”. International Conference on Green Intelligent Transportation Systems and Safety (GITSS), 2019.
[5]      H. Lin, W. Shi, H. Huang*, D. Zhuang*, S. Zhang, Y. Liu, X. Qu, J. Zhao. “Risk-Controllable Multi-View Diffusion for Driving Scenario Generation”. CVPR 2026 Workshop, 2026.

[6]      Z. Li, H. Huang*, H. Cheng, J. Jiang, X. Li, A. Zgonnikov. “Human Decision-Making in High-Risk Driving Scenarios: A Cognitive Modeling Perspective”. IEEE International Automated Vehicle Validation Conference (IAVVC), 2024.
[7]      H. Li, H. Huang*, X. Sun, X. Li. “Deception for Advantage in Connected and Automated Vehicle Decision-Making Games”. IEEE Intelligent Vehicles Symposium (IV), 2024.
[8]      H. Zhou, H. Huang*, P. Zhang, H. Shi, K. Long, X. Li*. “Online Physical Enhanced Residual Learning for Connected Autonomous Vehicles Platoon Centralized Control”. IEEE IV, 2024.
[9]      Y. Yang, M. Fan, C. He, J. Wang, H. Huang*, G. Sartoretti. “Attention-based Priority Learning for Limited Time Multi-Agent Path Finding”. Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024.

Awards

Selected Awards and Recognitions

  • 2024 Beijing Municipal Science and Technology Progress Award, First Prize
  • 2023 Best Paper Award, IEEE DSInS
  • 2023 Distinguished Ph.D. Graduate Awardee, Ministry of Education of Beijing
  • 2023 “Academic Rising Star” Award, School of Vehicle and Mobility, Tsinghua University
  • 2023 Best Ph.D. Thesis Award Finalist, National Ph.D. Academic Forum of the China Society of Automotive Engineers
  • 2022 ASCE Best Research Award for Risk and Uncertainty in Engineering Systems
  • 2022 Infineon Innovation Scholarship
  • 2022 Journal Cover Paper Award
  • 2022 Comprehensive First-Class Scholarship, Tsinghua University
  • 2022 Doctoral Forum Outstanding Thesis Award, Tsinghua University
  • 2021 Best Paper Award, Accident Analysis and Prevention
  • 2021 Comprehensive First-Class Scholarship, Tsinghua University
  • 2021 Doctoral Forum Outstanding Thesis Award, Tsinghua University
  • 2020 National Scholarship for Graduates, Ministry of Education of China
  • 2019 Youth Leadership Development Programme, ITS World Congress, Singapore
  • 2019 Comprehensive First-Class Scholarship, Tsinghua University
  • 2019 Doctoral Forum Outstanding Thesis Award, Tsinghua University
  • 2018 Distinguished Graduate, Outstanding Graduate Thesis, Central South University
  • 2017 Top 10 Outstanding Student Award, Central South University
  • 2016 Outstanding Student Pacesetter, Central South University
  • 2015 National Scholarship for Undergraduates, Ministry of Education of China

Research

  • Safe and trustworthy autonomous driving in safety-critical environments
  • Risk perception, cognition, and decision-making for autonomous driving
  • Generative AI and world models for prediction, reasoning, and long-tail scenario generation
  • Structured memory, retrieval, and hybrid rule-LLM reasoning for autonomous systems
  • Foundation models and embodied agents for robotics and intelligent mobility
  • Cognitive modeling and behavior understanding of human drivers and autonomous agents
  • Multi-agent interaction modeling for dense safety-critical environments

Teaching

Students