Dr Yanlong Huang
- Position: Associate Professor
- Areas of expertise: Imitation learning; Reinforcement learning.
- Email: Y.L.Huang@leeds.ac.uk
- Phone: +44(0)113 343 3505
- Location: 2.21C Sir William Henry Bragg Building
- Website: GitHub | Googlescholar | Researchgate
Profile
I am an Associate Editor for
- IEEE Transactions on Robotics
- IEEE Transactions on Automation Science and Engineering
Previously served as an Associate Editor for
- IEEE Robotics and Automation Letters (2021–2026)
Prospective students
I am looking for highly self-motivated and passionate PhD students who are interested in the following topics: imitation learning, deep reinforcement learning, large language model, computer vision, optimal control.
Application: send me your CV, BSc, and MSc transcripts in your enquiry email. You may visit our lab, but please make an appointment with one of my PhD students.
Preprints
- M. Mühlbauer, A. Sachtler, M. Knauer, C. Küçükgenç, Y. Huang, A. Albu-Schäffer, and J. Silvério. Fast non-parametric heteroscedastic imitation learning with geometric priors, arXiv:2610.08650, 2026.
- G. Li, P. Xu, R. Wang, Q. Ye, J. Chen, D. Song, and Y. Huang. Orientation learning and adaptation towards simultaneous incorporation of multiple local constraints, arXiv:2510.07986, 2025.
- Y. Huang. EKMP: Generalized imitation learning with adaptation, nonlinear hard constraints and obstacle avoidance, arXiv:2103.00452, 2021.
Selected Publications
- S. Wu, C. Liu, Y. Wang, C. Zhang, L. Han, and Y. Huang. Robust hybrid diffusion: unifying task space and joint space for robot manipulation, IEEE Robotics and Automation Letters (RA-L), 2026.
- Y. Wang, S. Wu, C. Liu, C. Zhang, J. Silvério, and Y. Huang. A computationally efficient nonparametric approach for robot imitation learning, IEEE International Conference on Robotics and Automation (ICRA), 2026. [video]
- S. Wu, Y. Wang, and Y. Huang. One-Shot robust imitation learning for long-horizon visuomotor tasks from unsegmented demonstrations, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025. [video]
- S. Wu, Y. Wang, and Y. Huang. Auto-LfD: closing the loop for learning from demonstrations, IEEE Transactions on Automation Science and Engineering (T-ASE), 2025. [video]
- J. Silvério and Y. Huang. A non-parametric skill representation with soft null space projectors for fast generalization, IEEE International Conference on Robotics and Automation (ICRA), 2023.
- P. Xu, L. Ding, Z. Li, J. Shi, H. Gao, G. Liu, and Y. Huang. A closed-loop shared control framework for legged robots, IEEE Transactions on Mechatronics (T-MECH), 2023.
- J. Ding, T. Lam, L. Ge, J. Pang, and Y. Huang. Safe and adaptive 3D locomotion via constrained task space imitation learning, IEEE Transactions on Mechatronics (T-MECH), 2023.
- F. J. Abu-Dakka, Y. Huang, J. Silvério, and V. Kyrki. A probabilistic framework for learning geometry-based robot manipulation skills, Robotics and Autonomous Systems (RAS), 2021. [video]
- Y. Huang, F. J. Abu-Dakka, J. Silvério, and D. G. Caldwell. Towards orientation learning and adaptation in Cartesian space, IEEE Transactions on Robotics (T-RO), 2020. [page]
- J. Ding, X. Xiao, N. Tsagarakis, and Y. Huang. Robust gait synthesis combining constrained optimization and imitation learning, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
- Y. Huang and D. G. Caldwell. A linearly constrained nonparametric framework for imitation learning, IEEE International Conference on Robotics and Automation (ICRA), 2020. [video]
- J. Silvério, Y. Huang, F. J. Abu-Dakka, L. Rozo, D. G. Caldwell. Uncertainty aware imitation learning using kernelized movement primitives, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019. [video][code]
- Y. Huang, L. Rozo, J. Silvério, and D. G. Caldwell. Kernelized movement primitives, The International Journal of Robotics Research (IJRR), 2019. [video][code]
- Y. Huang, F. J. Abu-Dakka, J. Silvério, and D. G. Caldwell. Generalized orientation learning in robot task space, IEEE International Conference on Robotics and Automation (ICRA), 2019. [video][code]
- Y. Huang, L. Rozo, J. Silvério, and D. G. Caldwell. Non-parametric imitation learning of robot motor skills, IEEE International Conference on Robotics and Automation (ICRA), 2019. [code]
- Y. Huang, J. Silvério, and D. G. Caldwell. Towards minimal intervention control with competing constraints, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
- J. Silvério, Y. Huang, L. Rozo, and D. G. Caldwell. An uncertainty-aware minimal intervention control strategy learned from demonstrations, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018. [video]
- J. Silvério, Y. Huang, L. Rozo, S. Calinon, and D. G. Caldwell. Probabilistic learning of torque controllers from kinematic and force constraints, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018. [video]
- Y. Huang, J. Silvério, L. Rozo, and D. G. Caldwell. Generalized task-parameterized skill learning, IEEE International Conference on Robotics and Automation (ICRA), 2018. [video]
- Y. Huang, J. Silvério, L. Rozo, and D. G. Caldwell. Hybrid probabilistic trajectory optimization using null-space exploration, IEEE International Conference on Robotics and Automation (ICRA), 2018. [video]
Research interests
Student education
COMP5611M Machine Learning (Module Leader)
COMP3631 Intelligent Systems and Robotics (Module Leader)
COMP5200M MSc Project
COMP3931/3932 Individual Project