I am Teng Xue, a final-year PhD student at Ecole Polytechnique Federale de Lausanne (EPFL) and a research assistant at Robot Learning and Interaction Group (RLI), Idiap Research Institute, supervised by Dr. Sylvain Calinon. Before joining Idiap/EPFL, I was fortunate to work as a visiting student at ETH RSL and Stanford Artificial Intelligence Lab (SAIL). I did my internships in DJI (2016), Flexiv Robotics (2021) and Meta Reality Labs (2025-2026). I am on the job market this year! Feel free to reach out.
My research focuses on compositional intelligence for robot generalization: enabling robots to construct complex behaviors by combining reusable models, skills, and constraints rather than learning each task from scratch. I am particularly interested in different forms of composition, including product of experts for combining task constraints, mixture of models for representing multimodal behaviors, and the sequencing of task-agnostic skills for long-horizon manipulation. My work explores how such compositional structures can support planning and control in contact-rich robotic systems, where nonlinear dynamics, hybrid contact modes, and physical uncertainty make generalization particularly challenging. To this end, I draw on tools spanning tensor networks, generative models, symbolic AI, optimal control, and learning from demonstration. These ideas have been studied across a range of dexterous and long-horizon manipulation problems, including planar pushing, object reorientation, block assembly, and bimanual manipulation.
Recent News
New (2026/01) Our workshop Workshop on Manipulation Robustness: Towards Human-Level Robustness under Real-World Challenges is accepted to ICRA 2026.
New (2025/10) Our paper Sampling-Based Constrained Motion Planning with Product of Experts is accepted to International Journal of Robotics Research (IJRR)!
New (2025/10) Our paper Learning Problem Decomposition for Efficient Sequential Multi-object Manipulation Planning is accepted to IEEE Robotics and Automation Letters (RA-L)!
New (2025/04) Our paper Robust Contact-rich Manipulation through Implicit Motor Adaptation is accepted to International Journal of Robotics Research (IJRR)!
(2024/09) Our paper Robust Manipulation Primitive Learning via Domain Contraction is accepted to Conference on Robot Learning (CoRL), 2024!
(2024/08) Our paper Design and Control of Roller Grasper V3 for In-Hand Manipulation is accepted to IEEE Transactions on Robotics (T-RO)!
(2024/06) Our paper Logic-Geometric Planning and Control Using Graph of Tensor Networks is accepted to RSS24 workshop: Frontiers of optimization for robotics !
(2024/06) Our paper Logic Learning from Demonstrations for Multi-step Manipulation Tasks in Dynamic Environments is accepted to RA-L!
(2024/05) Our paper Logic-Skill Programming: An Optimization-based Approach to Sequential Skill Planning is accepted to Robotics: Science and Systems (RSS), 2024!
(2024/02) I was fortunate to visit TU Berlin and give a talk at the Learning and Intelligent Systems research lab, led by Prof. Marc Toussaint .
(2024/01) Our paper D-LGP: Dynamic Logic-Geometric Program for Combined Task and Motion Planning is accepted to ICRA 2024!
(2024/01) Our paper Generalized Policy Iteration using Tensor Approximation for Hybrid Control is accepted to ICLR 2024 as spotlight (Top 5%)!
(2023/01) Our paper Demonstration-guided Optimal Control for Long-term Non-prehensile Planar Manipulation is accepted to ICRA 2023!
(2022/01) One paper about Robot Grasping in Dense Clutter is accepted to Robotics and Autonomous Systems!
(2020/05) One paper about Multimodel Fusion in pHRI is accepted to IEEE sensors journal!
(2020/02) One paper about Sequential Robot Manipulation is accepted to IEEE Access!
(2019/05) One paper about Tactile Grasping is accepted to ViTac workshop in ICRA 2019!
(2018/05) Our team, Kaibot, won the First Place in Tidy Up My Room Challenge in ICRA 2018!
(2017/02) We won the Outstanding Winner (1/8085) of MCM/ICM competition held by American Consortium for Mathematics and Its Application (COMAP). A nice collaboration with Yasheng and Taihang!