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Mr Xintong Yang
Teams and roles for Xintong Yang
Post-Doctoral Research Associate
Post Doctoral Research Associate
Overview
I’m a research associate (postdoc) in the School of Engineering at Cardiff University. I’m excited about enabling robots to manipulate real-world objects, rigid or deformable, through learning or non-learning methods. I studied deep (hierarchical) reinforcement learning and affordance learning for rigid object grasping and manipulation throughout my PhD years at Cardiff University and received my PhD in October, 2023. Now I’m developing methods to simulate and handle real-world deformable objects with differentiable physics. I also devote myself to open-source software development. Before my PhD, I received my Bachelor's and Master's degrees in Mechanical and Industrial Engineering from Guangdong University of Technology in China.
Publication
2025
- Han, S. et al., 2025. Dual-wave hybrid acoustofluidic centrifuge for rapid enrichment of micro- and nanoscale biological particles. Sensors and Actuators A: Physical 389 116495. (10.1016/j.sna.2025.116495)
- Wei, M. et al. 2025. A physics-informed demonstration-guided learning framework for granular material manipulation. IEEE Transactions on Neural Networks and Learning Systems (10.1109/tnnls.2025.3622482)
- 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.
- 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.
- Wu, Z. et al., 2025. Label-free DNA detection using optical barcodes from high Q-factor microbubble resonators. IEEE Sensors Journal 25 (14), pp.26631-26641. (10.1109/jsen.2025.3577175)
- 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 (10.1109/TRO.2025.3636815)
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. 2023. Robotic object manipulation via hierarchical and affordance learning. PhD Thesis , Cardiff University.
- 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)
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)
- 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)
- 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)
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
- 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)
- Han, S. et al., 2025. Dual-wave hybrid acoustofluidic centrifuge for rapid enrichment of micro- and nanoscale biological particles. Sensors and Actuators A: Physical 389 116495. (10.1016/j.sna.2025.116495)
- Wei, M. et al. 2025. A physics-informed demonstration-guided learning framework for granular material manipulation. IEEE Transactions on Neural Networks and Learning Systems (10.1109/tnnls.2025.3622482)
- Wu, Z. et al., 2025. Label-free DNA detection using optical barcodes from high Q-factor microbubble resonators. IEEE Sensors Journal 25 (14), pp.26631-26641. (10.1109/jsen.2025.3577175)
- 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. 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)
- 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. et al. 2025. DDBot: differentiable physics-based digging robot for unknown granular materials. IEEE Transactions on Robotics (10.1109/TRO.2025.3636815)
- 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)
- 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)
Conferences
- 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.
- 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.
- 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)
- 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)
- 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)
Thesis
- Yang, X. 2023. Robotic object manipulation via hierarchical and affordance learning. PhD Thesis , Cardiff University.
Research
I’m excited about enabling robots to manipulate real-world objects, rigid or deformable, through learning or non-learning methods. I studied deep (hierarchical) reinforcement learning and affordance learning for rigid object grasping and manipulation. Now I’m developing methods to simulate and handle real-world deformable objects.