Hao E. Zhang

Hao E. Zhang

Ph.D.
Research Fellow

I am a Research Associate in the Safe AI Lab at Carnegie Mellon University, working with Prof. Ding Zhao. I serve as the Associate Director of the ETAIC (Embodied Technology for Autonomy, Intelligence, and Control) Lab at the University of Texas at Arlington, working with Prof. Eric Tseng, a member of the National Academy of Engineering. Prior to this, I worked as a Research Fellow at Tsinghua University and a Visiting Researcher at University College London. I graduated from the School of Vehicle and Mobility at Tsinghua University, under the supervision of Prof. Zhi Wang and Prof. Shengbo Eben Li.

I was the recipient of the Outstanding Doctoral Dissertation Award and the Outstanding Ph.D. Graduate Award at Tsinghua University, and was selected as a Shuimu Scholar. Since 2019, my research on human-robot interaction (HRI), advanced driver-assistance systems (ADAS), and energy management systems (EMS) has contributed to the real-world deployment of reinforcement learning in robotic and intelligent vehicle systems, with a focus on improving safety, energy efficiency, and user comfort. The control and learning systems I developed have been implemented in collaboration with leading companies, including General Motors (GM), BYD Auto, Dongfeng Motor, SAIC Motor, and start-up companies such as Hybot.

I have authored over 50 peer-reviewed SCI journal and conference papers. I serve as Guest Editor for several journals and as Associate Editor on the International Program Committee of several conferences including IEEE ITSC, IEEE IV, etc. My current research focuses on multi-agent reinforcement learning theory, the integration of vison-language-models with closed-loop control, and human–robot collaboration using game theory. I aim to advance human-centric trustworthy AI agents for real-world deployment in autonomous systems.

Open to casual collaborations if interests align, and open to bringing in RA/Volunteers to work with me at Safe AI Lab and ETAIC Lab.

💻 Research Interests

  • Physical AI Theory: reinforcement learning and control, learning stability and safety, and game theory.
  • Robotics Applications: whole-body control, loco-manipulation, human-robot interaction, and sim-to-real transfer.
  • Mobility Applications: reinforcement learning for autonomous/electric vehicles, safety evaluation, and digital twins.
Demo 1
Multi-Agent Safe Decision Making
Demo 3
Agile Whole-Body Control
Demo 2
Contact-Rich Loco-Manipulation
Demo 4
Intelligent Vehicle and Digital Twin

🔥 News

💬 Media

Hao Zhang delivering an academic talk
Trustworthy Embodied Intelligence

Academic Talk

Research at the intersection of learning, control, and robotics for safe and capable intelligent systems in the physical world.

Watch Video →
Research featured by Carnegie Mellon University
Research & Impact

Institutional Feature

Selected research featured by academic institutions, highlighting advances in learning, robotics, and embodied intelligence.

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Recent Talks

  • 2026.09, Oral Presentation, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2026, “Interaction-Orientated Whole-Body Control for Compliant Object Transport”, Pittsburgh, USA
  • 2026.09, Oral Presentation (Best Paper Award), International Symposium on Advanced Vehicle Control (AVEC) 2026, “Intention-Aware Adversarial Multi-Agent Reinforcement Learning for Autonomous Vehicle Stress Testing”, Tsukuba, Japan
  • 2026.07, Oral Presentation, International Conference on Machine Learning (ICML) 2026, “HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization”, Seoul, South Korea
  • 2024.08, Plenary Talk, APC 2024: Joint Annual Conference on Advanced Powertrains - China SAE, “Data-Driven Modeling of Electric Vehicles and Reinforcement Learning-Based Optimal Control”, China SAE, Zhenjiang, China
  • 2024.05, Seminar Talk, “Reinforcement Learning-based Control and Policy Transfer for Connected Electric Vehicles”, Tsinghua University, Beijing, China

📝 Featured Publications

ICML (Oral)
sym

Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization

Hao Zhang, Yaru Niu, Yikai Wang, Ding Zhao, H. Eric Tseng
ICML 2026 Oral Presentation (top 0.7%)

Project Webpage

  • We propose heterogeneous-agent Lyapunov policy optimization (HALO), which establishes formal stability directly in the policy-parameter space by enforcing a per-step Lyapunov decrease condition on a parameter-space disagreement metric.
Preprint
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C2C: A Cognition-to-Control Hierarchy for Human-Robot Collaboration via Multi-Agent Learning

Hao Zhang, Ding Zhao, H. Eric Tseng
Under review

Project Webpage

  • In multi-agent human-robot collaboration, where long-horizon coordination decisions and physical execution must co-evolve under contact, feasibility, and safety constraints. We address this limitation with cognition-to-control (C2C), a three-layer hierarchy that makes the deliberation-to-control pathway explicit.
IEEE/RSJ IROS
sym

Learning Versatile Humanoid Manipulation with Touch Dreaming

Yaru Niu, Zhenlong Fang, Binghong Chen, Shuai Zhou, Revanth Senthilkumaran, Hao Zhang, Bingqing Chen, Chen Qiu, Eric H. Tseng, Jonathan Francis, Ding Zhao
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2026

Project Webpage

  • We develop a VR-based whole-body data collection system and propose Humanoid Transformer with Touch Dreaming (HTD), a multimodal Transformer that jointly models vision, proprioception, and touch, achieving a 90.9% relative improvement in average success rate across five real-world tasks.
IEEE/RSJ IROS
sym

IO-WBC: Interaction-Orientated Whole-Body Control for Compliant Object Transport

Hao Zhang, Yves Tseng, Ding Zhao, H. Eric Tseng
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2026

Project Webpage

  • We proposed a bio-inspired, interaction-oriented whole-body control (IO-WBC) that functions as an artificial cerebellum - an adaptive motor agent that translates upstream (skill-level) commands into stable, physically consistent whole-body behavior under contact.
IEEE TITS
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Multi-Scale Reinforcement Learning of Dynamic Energy Controller for Connected Electrified Vehicles

Hao Zhang, Nuo Lei, Shengbo Eben Li, Junzhi Zhang, Zhi Wang
In IEEE Transactions on Intelligent Transportation Systems

  • We proposed a multi-horizon reinforcement learning (MHRL) featuring a novel state representation and coordinated training of sub-networks across multiple time scales, which greatly improves fuel economy in real-world driving.
IEEE TITS
sym

Bi-Level Transfer Learning for Lifelong-Intelligent Energy Management of Electric Vehicles

Hao Zhang, Nuo Lei, Wang Peng, Bingbing Li, Shujun Lv, Boli Chen, Zhi Wang
In IEEE Transactions on Intelligent Transportation Systems

Industrial Collaborator: BYD Auto

  • We proposed a bi-level transfer approach with MAML to realize cross-platform transferable and online-adaptive EMS for REEVs. It contributed to the successful industry deployment of RL methods, implemented in leading automotive company - BYD Auto, significantly enhancing the REEV efficiency.

Book Chapters

  • Hao Zhang, H. Eric Tseng. “Foundations of Human-Aware, Intention-Informed Stress Testing for Autonomous Vehicles.” Advances in Intelligent Vehicles in the Era of AI. Institution of Engineering and Technology (IET), To be published.
  • Bin Shuai*, Hao Zhang* (Co-first Author), Min Hua, Beiyan Jiang, Zhi Wang, Shengbo Eben Li. “Model-free reinforcement learning for integrated energy control of hybrid road vehicles.” Physics-Aware Machine Learning for Integrated Energy Systems Management. Elsevier, 2025. 299-331.

Selected Papers

  • Hao Zhang, Yaru Niu, Yikai Wang, Ding Zhao, H. Eric Tseng. HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization. International Conference on Machine Learning (ICML), 2026. Oral Presentation, top 0.7%.
  • Hao Zhang, Yves Tseng, Ding Zhao, H. Eric Tseng. IO-WBC: Interaction-Orientated Whole-Body Control for Compliant Object Transport. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026, Oral Presentation.
  • Hao Zhang, H. Eric Tseng. Intention-Aware Adversarial Multi-Agent Reinforcement Learning for Autonomous Vehicle Stress Testing. International Symposium on Advanced Vehicle Control (AVEC), 2026, Oral Presentation, Best Paper Award.
  • Yaru Niu, Zhenlong Fang, Binghong Chen, Shuai Zhou, Revanth Senthilkumaran, Hao Zhang, Bingqing Chen, Chen Qiu, H. Eric Tseng, Jonathan Francis, Ding Zhao. Learning Versatile Humanoid Manipulation with Touch Dreaming. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026, Oral Presentation.
  • Hao Zhang, Nuo Lei, Shengbo Eben Li, Junzhi Zhang, Zhi Wang. Multi-Scale Reinforcement Learning of Dynamic Energy Controller for Connected Electrified Vehicles. IEEE Transactions on Intelligent Transportation Systems, 2025, 26(12): 22607–22619. (IF: 9.1)
  • Hao Zhang, Ding Zhao, H. Eric Tseng. Cognition-to-Control: Multi-Agent Learning for Human-Humanoid Collaborative Transport. arXiv:2603.03768, 2026. Preprint.
  • Guoke Luo, Hao Zhang† (Corresponding author). Adaptive Bipedal Locomotion on Time-Varying Footholds. IEEE-RAS International Conference on Humanoid Robots, 2026, Preprint.
  • Hao Zhang, Nuo Lei, Wang Peng, Bingbing Li, Shujun Lv, Boli Chen, Zhi Wang. Bi-Level Transfer Learning for Lifelong-Intelligent Energy Management of Electric Vehicles. IEEE Transactions on Intelligent Transportation Systems, 2025, 26(10): 16174–16187. (IF: 9.1)
  • Guixiang Yang, Hao Zhang, Lin Qiu. Graph-Based Multi-Agent Reinforcement Learning with an Enriched Environment for Joint Ride-Sharing and Charging Optimization. Applied Energy, 2026, 405: 127220. (IF: 12.2)
  • Hao Zhang, Guixiang Yang, Nuo Lei, Chaoyi Chen, Boli Chen, Lin Qiu. Scenario-Aware Electric Vehicle Energy Control with Enhanced Vehicle-to-Grid Capability: A Multi-Task Reinforcement Learning Approach. Energy, 2025, 335: 138189. (IF: 10.1)
  • Yuhan Chen, Yuhao Liu, Nuo Lei, Chaoyi Chen, Hao Zhang† (Project lead & Corresponding author). Knowledge-Interposed Curriculum Reinforcement Learning for Efficient Supervisory Control Synthesis in Electric Flying Vehicles. Green Energy and Intelligent Transportation, 2026, Early Access. (IF: 21.5)
  • Nuo Lei, Hao Zhang† (Project lead & Corresponding author), Hong Wang, Zunyan Hu, Hu Chen, Jingjing Hu, Zhi Wang. Theory-Constrained Neural Network with Modular Interpretability for Fuel Cell Vehicle Modeling. IEEE Transactions on Vehicular Technology, 2025, 74(6): 8907–8920. (IF: 7.5)
  • Hao Zhang, Boli Chen, Nuo Lei, Bingbing Li, Rulong Li, Zhi Wang. Integrated Thermal and Energy Management of Connected Hybrid Electric Vehicles Using Deep Reinforcement Learning. IEEE Transactions on Transportation Electrification, 2024, 10(2): 4594–4603. (IF: 8.5)
  • Guixiang Yang, Hao Zhang, Lin Qiu. Joint Taxi Dispatch and Station Pricing Optimization: A Game-Theoretic Multi-Agent Reinforcement Learning Approach via Alternating Training. Energy, 2026, Article 140715. (IF: 10.1)
  • Yuanhanxu Song, Xiang Gao, Hao Zhang† (Corresponding author). Coordination Residual Learning for Multi-Humanoid Loco-Manipulation. IEEE-RAS International Conference on Humanoid Robots, 2026, Preprint.
  • Hao Zhang, Jiawen Dong, Nuo Lei, Yikun Qin, Bingbing Li, Chaoyi Chen, Boli Chen. Optimal Vehicle Dynamics and Powertrain Control of Carbon-Free Autonomous Vehicles: Large Language Model Assisted Heterogeneous-Agent Learning. Energy, 2025, 338: 138786. (IF: 10.1)
  • Nuo Lei, Hao Zhang, Jingjing Hu, Zunyan Hu, Zhi Wang. Sim-to-Real Design and Development of Reinforcement Learning-Based Energy Management Strategies for Fuel Cell Electric Vehicles. Applied Energy, 2025, 393: 126030. ESI Highly Cited Paper. (IF: 12.2)
  • Hao Zhang, Boli Chen, Nuo Lei, Bingbing Li, Chaoyi Chen, Zhi Wang. Coupled Velocity and Energy Management Optimization of Connected Hybrid Electric Vehicles for Maximum Collective Efficiency. Applied Energy, 2024, 360: 122792. (IF: 12.2)
  • Nuo Lei, Hao Zhang, Hong Wang, Zhi Wang. An Improved Co-Optimization of Component Sizing and Energy Management for Hybrid Powertrains Interacting with High-Fidelity Model. IEEE Transactions on Vehicular Technology, 2023, 72(12): 15585–15596. (IF: 7.5)
  • Bingbing Li, Weichao Zhuang, Hao Zhang, Hao Sun, Haoji Liu, Jianrun Zhang, Guodong Yin, Boli Chen. Traffic-Aware Ecological Cruising Control for Connected Electric Vehicle. IEEE Transactions on Transportation Electrification, 2024, 10(3): 5225–5240. (IF: 8.5)
  • Hao Zhang, Nuo Lei, Boli Chen, Bingbing Li, Rulong Li, Zhi Wang. Modeling and Control System Optimization for Electrified Vehicles: A Data-Driven Approach. Energy, 2024, 310: 133196. (IF: 10.1)
  • Hao Sun, Bingbing Li, Hao Zhang, Li Dai, Giuseppe Fedele, Weichao Zhuang, Boli Chen. Ecological Electric Vehicle Platooning: An Adaptive Tube-Based Distributed Model Predictive Control Approach. IEEE Transactions on Transportation Electrification, 2024, 11(1): 1048–1060. (IF: 8.5)

The above are selected recent publications from the past 3 years. A complete publication list is available on my Google Scholar homepage.

🎖 Honors and Awards

  • 2026 Best Paper Award at International Symposium on Advanced Vehicle Control
  • 2026 Oral Presentation at International Conference on Machine Learning
  • 2026 Gold Reviewer for International Conference on Machine Learning
  • 2024 Plenary Talk at 2024 China SAE Annual Conference on Advanced Powertrains
  • 2024 “Shuimu Tsinghua Scholar” Talents Program, Tsinghua University
  • 2024 Outstanding Doctoral Dissertation Award, Tsinghua University
  • 2024 Outstanding Ph.D. Graduate (top 4%), Tsinghua University
  • 2023 Comprehensive Excellence Scholarship, Tsinghua University
  • 2022 Comprehensive Excellence Scholarship, Tsinghua University
  • 2021 Excellent Student Leader, Tsinghua University
  • 2021 Comprehensive Excellence Scholarship, Tsinghua University
  • 2020 Comprehensive Excellence Scholarship, Tsinghua University
  • 2018 National Scholarship, Ministry of Education of China
  • 2018 Best Paper Award in the 2018 IEEE ACES Conference in Denver, U.S.
  • 2017 National Scholarship, Ministry of Education of China
  • 2016 National Scholarship, Ministry of Education of China

📚 Service

Reviewer

  • Associate Editor: IEEE Intelligent Vehicles Symposium (IEEE IV), sponsored by The IEEE Intelligent Transportation Systems Society (ITSS), Ann Arbor, USA
  • Associate Editor: The IEEE International Conference on Intelligent Transportation Systems (ITSC), sponsored by The IEEE Intelligent Transportation Systems Society (ITSS), Naples, Italy
  • Guest Editor: Electronics, Special Issue: Eco-Safe Intelligent Mobility Development and Application
  • Journal Reviewer: 1. IEEE Transactions on Intelligent Transportation Systems (IF: 9.1); 2. IEEE Transactions on Intelligent Vehicles (IF: 14.3); 3. IEEE Transactions on Transportation Electrification (IF: 8.5); 4. IEEE Transactions on Visualization and Computer Graphics (IF: 6.8); 5. IEEE Open Journal of Vehicular Technology (IF: 6.6); 6. Renewable and Sustainable Energy Reviews (IF: 18.0); 7. Applied Energy (IF: 12.2); 8. Energy (IF: 10.1); 9. Energy Conversion and Management (IF: 11.8); 10. Sustainable Energy, Grids and Networks (IF: 5.7); 11. Journal of Cleaner Production (IF: 10.7); 12. Journal of Energy Storage (IF: 10.7); 13. Journal of Power Sources (IF: 8.4); 14. Green Energy and Intelligent Transportation (IF: 21.5); 15. Robotics and Autonomous Systems (IF: 6.0); 16. Engineering Applications of Artificial Intelligence (IF: 9.0); 17. eTransportation (IF: 18.7)
  • Conference Reviewer: 1. International Conference on Machine Learning (ICML); 2. Annual Conference on Neural Information Processing Systems (NeurIPS); 3. AAAI Conference on Artificial Intelligence (AAAI); 4. IEEE Intelligent Vehicles Symposium (IV); 5. IEEE Intelligent Transportation Systems Conference (ITSC)

Teaching

  • Guest Lecturer (Designed and delivered 6 lectures), EE5329, Topics in Systems Engineering (Reinforcement Learning and Control), UT Arlington, Spring 2026
  • Guest Lecturer (Project-based instruction), 80150183, Fundamentals of Automotive Powertrains, Tsinghua University, Fall 2023
  • Teaching Assistant, 40150420, Student Research Training (SRT), Tsinghua University, Fall 2022
  • Teaching Assistant, 80150042, Frontiers in Vehicle System Dynamics and Control, Tsinghua University, Fall 2021

Mentorship

  • Since 2024 (during Postdoc), have independently provided mentorship to postgraduate and undergraduate students (research assistants): Mr. Ruize Geng (JHU), Mr. Yisen Li (UPenn), Mr. Changwei Yao (CMU), MS. Jiayi Liu (Tsinghua University), Mr. Yuhan Chen (UC Berkeley), Mr. Kaifeng Jia (Cornell University), Ms. Xinyi Zhao (NYU), Ms. Siting Xu (Duke), Mr. Jiarui Zhang (HKU), Ms. Guixiang Yang (Zhejiang University), etc. More than half of the mentees have published papers in top-tier conferences and journals, with me serving as the corresponding/last author on multiple projects. I am actively recruiting research assistants and students interested in embodied AI.
  • Since 2020, assisted in the supervision of 5 Ph.D. students, 13 master’s students; mentored over a dozen undergraduate students, their work received multiple honors including Tsinghua University and Beijing Outstanding Undergraduate Thesis Awards.