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Dr Xintong Yang
(he/him)
PhD (Cardiff)
Teams and roles for Xintong Yang
Lab Manager (Robotics and Autonomous Systems Lab)
Post-Doctoral Research Associate
Overview
I am a Research Associate working across the School of Engineering and the School of Pharmacy and Pharmaceutical Sciences at Cardiff University. I am also a Fellow of the Higher Education Academy (FHEA) and Lab Manager of the Robotics and Autonomous Systems Laboratory, based in Room C1.06, Queen’s Buildings.
My research focuses on developing reliable robotic systems for manipulating rigid, deformable and granular materials. I combine guided agentic engineering, differentiable physics-based modelling and learning-based methods to enable robots to operate autonomously and robustly in complex real-world environments. I also develop simulation tools for enzymatic reactions and robotic systems for laboratory automation.
I completed my PhD at Cardiff University in October 2023. My doctoral research investigated deep hierarchical reinforcement learning and affordance learning for robotic manipulation. Before joining Cardiff, I obtained Bachelor’s and Master’s degrees in Mechanical and Industrial Engineering from Guangdong University of Technology, China.
Research interests
- Guided agentic engineering for real-world robot autonomy
- Manipulation of deformable and granular materials
- Differentiable physics and system identification
- Model- and data-driven methods for long-horizon manipulation
- Affordance-guided robotic perception and action
- Reliable robotic systems for human-facing, real-world applications
- Robotic laboratory automation and enzymatic reaction simulation
Publication
2026
- Wei, M. et al. 2026. A physics-informed demonstration-guided learning framework for granular material manipulation. IEEE Transactions on Neural Networks and Learning Systems 37 (4), pp.1590-1604. (10.1109/tnnls.2025.3622482)
2025
- Yang, X. , Ji, Z. and Lai, Y. 2025. Differentiable physics-based system identification for robotic manipulation of elastoplastic materials. International Journal of Robotics Research 44 (13), pp.2126-2155. (10.1177/02783649251334661)
- Yang, X. et al. 2025. DDBot: differentiable physics-based digging robot for unknown granular materials. IEEE Transactions on Robotics 42 , pp.152-169. (10.1109/TRO.2025.3636815)
- Wei, M. et al. 2025. Celebi’s choice: causality-guided skill optimisation for granular manipulation via differentiable simulation. Presented at: IROS 2025 Hangzhou, China 19-25 October 2025. Proceedings of the 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025). IEEE.
- Wei, M. et al. 2025. Differentiable skill optimisation for powder manipulation in laboratory automation. Presented at: IEEE/RSJ International Conference on Intelligent Robots and Systems Hangzhou, China 19-25 October 2025.
2024
- Gao, Y. et al. 2024. Efficient hierarchical reinforcement learning for mapless navigation with predictive neighbouring space scoring. IEEE Transactions on Automation Science and Engineering 21 (4), pp.5457-5472. (10.1109/TASE.2023.3312237)
- Yang, X. and Ji, Z. 2024. Accelerating multi-step sparse reward reinforcement learning. Presented at: Cardiff University Engineering Research Conference 2023 Cardiff, UK 12-14 July 2023. Published in: Spezi, E. and Bray, M. eds. Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press. , pp.86-90. (10.18573/conf1.u)
- Yang, X. et al. 2024. GAM: General Affordance-based Manipulation for contact-rich object disentangling tasks. Neurocomputing 578 127386. (10.1016/j.neucom.2024.127386)
2023
- Yang, X. et al. 2023. Recent advances of deep robotic affordance learning: a reinforcement learning perspective. IEEE Transactions on Cognitive and Developmental Systems 15 (3), pp.1139-1149. (10.1109/TCDS.2023.3277288)
- Yang, X. 2023. Robotic object manipulation via hierarchical and affordance learning. PhD Thesis , Cardiff University.
- Zhang, T. et al., 2023. Home health care routing and scheduling in densely populated communities considering complex human behaviours. Computers and Industrial Engineering 182 109332. (10.1016/j.cie.2023.109332)
2022
- Yang, X. et al. 2022. Abstract demonstrations and adaptive exploration for efficient and stable multi-step sparse reward reinforcement learning. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022) Bristol, United Kingdom 1-3 September 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE. (10.1109/ICAC55051.2022.9911100)
- You, Y. et al. 2022. From human-human collaboration to human-robot collaboration: automated generation of assembly task knowledge model. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022) Bristol, UK 1-3 Sept 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE. (10.1109/ICAC55051.2022.9911131)
- Yang, X. et al. 2022. Hierarchical reinforcement learning with universal policies for multi-step robotic manipulation. IEEE Transactions on Neural Networks and Learning Systems 33 (9), pp.4727-4741. (10.1109/TNNLS.2021.3059912)
2021
- Yang, X. et al. 2021. An open-source multi-goal reinforcement learning environment for robotic manipulation with Pybullet. Presented at: 21st Towards Autonomous Robotic Systems Conference (TAROS 2021) Virtual 8-10 September 2021. Published in: Fox, C. et al., Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science Springer. , pp.14-24. (10.1007/978-3-030-89177-0_2)
Articles
- Wei, M. et al. 2026. A physics-informed demonstration-guided learning framework for granular material manipulation. IEEE Transactions on Neural Networks and Learning Systems 37 (4), pp.1590-1604. (10.1109/tnnls.2025.3622482)
- Yang, X. , Ji, Z. and Lai, Y. 2025. Differentiable physics-based system identification for robotic manipulation of elastoplastic materials. International Journal of Robotics Research 44 (13), pp.2126-2155. (10.1177/02783649251334661)
- Yang, X. et al. 2025. DDBot: differentiable physics-based digging robot for unknown granular materials. IEEE Transactions on Robotics 42 , pp.152-169. (10.1109/TRO.2025.3636815)
- Gao, Y. et al. 2024. Efficient hierarchical reinforcement learning for mapless navigation with predictive neighbouring space scoring. IEEE Transactions on Automation Science and Engineering 21 (4), pp.5457-5472. (10.1109/TASE.2023.3312237)
- Yang, X. et al. 2024. GAM: General Affordance-based Manipulation for contact-rich object disentangling tasks. Neurocomputing 578 127386. (10.1016/j.neucom.2024.127386)
- Yang, X. et al. 2023. Recent advances of deep robotic affordance learning: a reinforcement learning perspective. IEEE Transactions on Cognitive and Developmental Systems 15 (3), pp.1139-1149. (10.1109/TCDS.2023.3277288)
- Zhang, T. et al., 2023. Home health care routing and scheduling in densely populated communities considering complex human behaviours. Computers and Industrial Engineering 182 109332. (10.1016/j.cie.2023.109332)
- Yang, X. et al. 2022. Hierarchical reinforcement learning with universal policies for multi-step robotic manipulation. IEEE Transactions on Neural Networks and Learning Systems 33 (9), pp.4727-4741. (10.1109/TNNLS.2021.3059912)
Conferences
- Wei, M. et al. 2025. Celebi’s choice: causality-guided skill optimisation for granular manipulation via differentiable simulation. Presented at: IROS 2025 Hangzhou, China 19-25 October 2025. Proceedings of the 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025). IEEE.
- Wei, M. et al. 2025. Differentiable skill optimisation for powder manipulation in laboratory automation. Presented at: IEEE/RSJ International Conference on Intelligent Robots and Systems Hangzhou, China 19-25 October 2025.
- Yang, X. and Ji, Z. 2024. Accelerating multi-step sparse reward reinforcement learning. Presented at: Cardiff University Engineering Research Conference 2023 Cardiff, UK 12-14 July 2023. Published in: Spezi, E. and Bray, M. eds. Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press. , pp.86-90. (10.18573/conf1.u)
- Yang, X. et al. 2022. Abstract demonstrations and adaptive exploration for efficient and stable multi-step sparse reward reinforcement learning. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022) Bristol, United Kingdom 1-3 September 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE. (10.1109/ICAC55051.2022.9911100)
- You, Y. et al. 2022. From human-human collaboration to human-robot collaboration: automated generation of assembly task knowledge model. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022) Bristol, UK 1-3 Sept 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE. (10.1109/ICAC55051.2022.9911131)
- Yang, X. et al. 2021. An open-source multi-goal reinforcement learning environment for robotic manipulation with Pybullet. Presented at: 21st Towards Autonomous Robotic Systems Conference (TAROS 2021) Virtual 8-10 September 2021. Published in: Fox, C. et al., Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science Springer. , pp.14-24. (10.1007/978-3-030-89177-0_2)
Thesis
- Yang, X. 2023. Robotic object manipulation via hierarchical and affordance learning. PhD Thesis , Cardiff University.
Research
Real-world robotics heavily relies on sound system engineering facilitating the processing and communications of information among submodules that independently and/or collaboratively inform decisions to control a robot embodiment towards accomplishing certain tasks. My research focus on:
- 3D Perception & Action: how robots can perceive, understand and interact with the 3D world to accomplish a user-defined task?
- Autonuous & Resilient System Engineering: how autonomous systems can improve themselves by writing codes to understand and control different embodiments, environments and tasks?
- Safety: how can we prevent robots from misinterpreting user intents and perfroming dangerous actions?
Browse project showroom to see my past projects in learning/physics-based rigid and deformation obejct manipulation.
Involved research grants:
Title: Developing dRTP Leadership for Reliable AI-Driven Autonomous Laboratories
Role: Co-I, Lead Researcher | Total value: GBP 14,693.09
- Cardiff-Xiamen Collaboration Fund
- PHYDL: Physics-Guided Differentiable Learning for Robotic Manipulation of Deformable and Granular Materials
- Almond: Autonomous Laboratory for Molecular Discovery
Teaching
2023 - 2024
- EN3062 Robotics and Image Processing (Module lecturer)
- EN4062 Advanced Robotics (Module lecturer)
Biography
Professional memberships
Fellow of the Higher Education Academy (FHEA)
Supervisions
Past projects
Minglun Wei - Co-supervised PhD student, Cardiff University (ongoing) - Deformable Object Manipulation
Boliang Cai - Former co-supervised PhD student, now Research Associate at Loughborough University - Autonomous Vehicles
Contact Details
Research themes
Specialisms
- Robotics
- Machine learning
- Physics-informed Robotic Manipulation
- Robot learning
- Agentic research and engineering