Summary
Yijiong Lin is a Postdoctoral Research Associate at the Bristol Robotics Laboratory with nine years of experience focused on multimodal sensing and sim-to-real deep reinforcement learning for dexterous robotic manipulation. He led doctoral research on "Sim-to-Real Deep Tactile Policies" and now contributes to the ARIA-funded Democratising Co-Design of Hardware and Control for Robot Dexterity project under Professors Nathan Lepora and Edward Johns. His background blends engineering mathematics, mechanical engineering and hands-on robot learning—from an MEng and visiting research at UM-SJTU to a PhD from the University of Bristol—giving him a strong cross-disciplinary foundation in tactile sensing, control and policy transfer. He has taught and supervised robotics students, running critical-thinking seminars and assessments, which informs his practical approach to research translation. Notably, his work emphasizes combining tactile modalities with reinforcement learning to bridge simulation and real-world performance, aiming to make dexterous manipulation more accessible to wider research and engineering communities.
9 years of coding experience
Master of Engineering - MEng, Robotics, Master of Engineering - MEng, Robotics at Guangdong University of Technology
Doctor of Philosophy - PhD, Robotics, Doctor of Philosophy - PhD, Robotics at University of Bristol
English, Chinese, Chinese