Guoxin Fang (方国鑫)

Researcher in Robotics & Advanced Manufacturing

I am an Assistant Professor in the Department of Mechanical and Automation Engineering at The Chinese University of Hong Kong (CUHK). Before join CUHK, I worked as a Research Associate in the Digital Manufacturing Lab at the University of Manchester (UoM), and received Ph.D. degree from Delft University of Technology (TU Delft) , supervised by Prof. Charlie C.L. Wang and Prof. Jo Geraedts. I received my B.Eng. degree in Mechanical Engineering and Automation from Beijing Institute of Technology. I am a member of IEEE, ASME and ACM (SIGGRAPH).

We are seeking motivated researchers to join our research group - Computational Robotics and Manufacturing Lab. Postdoc Research Associate (topic: multi-robot collaboration for advanced manufacturing) and PhD positions (2 for 2025 intake) are available. Researchers who having experience in robot motion planning, geometry computing, machine learning, and additive manufacting are encouraged to apply.

As a researcher in the field of robotics and advanced manufacturing, my research aims at developing theoretical foundations and computational tools that will shape the future of robots and manufacturing systems. Main research topics include:

1) Robot-Assisted Advanced Manufacturing; 2) Soft Robot; 3) Computational Design for Multi-Functional (Wearable) Devices.

Selected Publication
Full list of the publications can be accessed on Google Scholar.

Robot-Assisted Advanced Manufacturing :

Learning based toolpath planner on diverse graphs for 3D printing,
ACM Transactions on Graphics, 2024. (project page)

Exceptional mechanical performance by spatial printing with continuous fiber, Additive Manufacturing, 2024. (project page)

Turning-angle optimized printing path of continuous carbon fiber for cellular structures, Additive Manufacturing, 2023.

Vector field based volume peeling for multi-axis machining, J-CISE 2023.
(Best Paper Award - ASME IDETC/CIE 2023 Conference)

S^3-Slicer: A general slicing framework for multi-axis 3D printing, ACM Transactions on Graphics, 2022. (project page)
(Best Paper Award - SIGGRAPH Asia 2022 Technical Papers)

Field-based toolpath generation for 3D printing continuous fibre reinforced thermoplastic composites, Additive Manufacturing, 2021.

Reinforced FDM: Multi-axis filament alignment with controlled anisotropic strength, ACM Transactions on Graphics, 2020. (project page)

Soft Robots:

Accelerate neural subspace-based reduced-order solver of deformable simulation by Lipschitz optimization, ACM Transactions on Graphics, 2024.

Function based sim-to-real learning for shape control of deformable free-form surfaces, Robotics: Science and Systems (RSS), 2024.

Spring-IMU fusion based proprioception for feedback control of soft manipulators, IEEE/ASME Transactions on Mechatronics , 2023.

Efficient Jacobian-based inverse kinematics with sim-to-real transfer of soft robots by learning, IEEE/ASME Transactions on Mechatronics, 2022.

Soft robotic mannequin: design and algorithm for deformation control, IEEE/ASME Transactions on Mechatronics, 2022.

Sensing and reconstruction of 3D deformation on pneumatic soft robots, IEEE/ASME Transactions on Mechatronics, 2021.

Kinematics of soft robots by geometric computing, IEEE Transactions on Robotics, 2020. (source code available)

Contact me via: guoxinfang@mae.cuhk.edu.hk
Address: Rm 112A, Ho Sin Hang Engineering Building, CUHK, Hong Kong SAR, China.