Guoxin Fang (方国鑫)

Assistant Professor, The Chinese University of Hong Kong
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 from Beijing Institute of Technology (BIT). I am a member of IEEE, ASME and ACM.

I am seeking for motivated researchers to join my research group - Computational Robotics and Manufacturing Lab. Postdoctoral and PhD/MPhil positions are available. Candidates should have a degree in Mechanical Engineering, Computer Science, or Mathematics. Researchers who having experience in additive manufacturing, robotics, machine learning, or geometry computing are encouraged to apply. [admission guide]

As a researcher in the field of robotics and advanced manufacturing, I've developed computational tools to enhance the intelligence of robot and (multi-axis) manufacturing systems. These tools enable the robots to operate more smartly and efficiently in manufacturing applications. The foundational knowledge underpinning my research includes numerical optimization, geometric computing, and machine learning.

My main research topics includes: 1) Multi-axis Additive Manufacturing; 2) Design, Modeling, Fabrication, and Control of Soft Robotics Systems. Please refer to my research statement for a brief description of my research.

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

Robot-assisted Advanced Manufacturing :

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. (source code available)
(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. (source code available)

Soft Robots:

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.