Scholar
Max Yang
Google Scholar ID: WQQ1vz8AAAAJ
University of Bristol
Citations & Impact
Citations
145
H-index
6
i10-index
6
Publications
13
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- [{'PaperTitle': 'AnyRotate: Gravity Invariant In-Hand Object Rotation with Sim-to-Real Touch', 'Conference': 'Conference of Robot Learning (CoRL) 2024'}, {'PaperTitle': 'Snap-it, Tap-it, Splat-it: Tactile-Informed 3D Gaussian Splatting for Reconstructing Challenging Surfaces', 'Status': 'Under Review 2024'}, {'PaperTitle': 'Bi-Touch: Bimanual Tactile Manipulation with Sim-to-Real Deep Reinforcement Learning', 'Journal': 'Robotics and Automation Letters (RA-L) 2023'}, {'PaperTitle': 'Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing', 'Journal': 'Robotics and Automation Letters (RA-L) 2023'}, {'PaperTitle': 'Tac-VGNN: A Voronoi Graph Neural Network for Pose-Based Tactile Servoing', 'Conference': 'International Conference on Robotics and Automation (ICRA) 2023'}]
Background
- PhD student in Robotics and AI at the University of Bristol. Current research focuses on sim-to-real deep reinforcement learning and tactile perception for robot manipulation. Interests lie in machine learning methods for robot perception and control.
Miscellany
- Interests include tactile sensing, dexterous manipulation, and sim-to-real deep reinforcement learning. Currently seeking PhD internships for Fall/Winter 2024.
