Publications

Robot-assisted multi-axis embedded silicone printing for free-form volumetric model

Hailin Sun, Yingjun Tian, Chenyu Xu, Mahdi Bodaghi, Fei Gao, and Guoxin Fang*

Virtual and Physical Prototyping, vol. 21, e2614811, 2026.

Best Fabrication Award 🏆, IEEE Robosoft Conference 2026

TL;DR Curved layers and width-controlled toolpaths enable robotic silicone printing of free-form solid parts with dense infill and accurate surfaces.

WildFab: Multi-Axis 3D Printing from Models in the Wild

Jiasheng Qu, Zhikai Shen, Chenyu Xu, Hailin Sun, Chengkai Dai, Yuhu Guo, Junpeng Wang, Yeung Yam, Guoxin Fang*

ACM Transactions on Graphics (To be presented at SIGGRAPH Asia 2026), no. 6, December 2026.

TL;DR Hybrid geometric fields turn imperfect and mixed solid–shell models directly into support-free toolpaths and collision-free robot motions, without mesh repair.

Thin-Film DLP 3D Printing of Multi-Material Parts with Closed-Cell Internal Voids

Binzhi Sun, Nicholas S. Diaco, Xiangjia Chen, Chengkai Dai, A. John Hart, Charlie C.L. Wang, Guoxin Fang*, and Yeung Yam*

NPJ Advanced Manufacturing, 3, 15 (2026).

TL;DR Casting and curing thin resin films replaces the vat, enabling multi-material DLP printing of enclosed hollow structures with minimal trapped resin.

RealSimLoop: Online Real-to-Sim Adaptation via Differentiable Reduced-Order Simulation with Vision Feedback

Zhihao Cen, Chuhua Xian*, Hailin Sun, Yuliang Liufu, Zhen Zhang, Xiangyu Chu, Hongmin Cai, Yunbo Zhang, and Guoxin Fang*

ACM SIGGRAPH Asia 2026, Dec, 2026, Malaysia.

TL;DR Vision feedback updates material parameters inside a differentiable reduced-order simulator online, enabling estimates of hidden deformation, stresses, and interaction forces.

Model-Free Co-Optimization of Manufacturable Sensor Layouts and Deformation Proprioception

Yingjun Tian, Guoxin Fang, Aoran Lyu, Xilong Wang, Zikang Shi, Yuhu Guo, Weiming Wang and Charlie C.L. Wang*

IEEE Transactions on Robotics, vol.42, pp.1662-1679, March 2026.

TL;DR Jointly optimizing sensor layouts and shape prediction produces sparse, manufacturable sensing systems that reconstruct deformation without requiring a physical simulation model.

Proximity3D: Shape from Capacitive Proximity on Sensing Manifold

Hao Chen, Chenming Wu, Chun Ping Lam, Xiangjia Chen, Guoxin Fang, Charlie C.L. Wang, Yeung Yam, Juncong Lin, Chengkai Dai*

ACM SIGGRAPH Asia 2026, December, 2026, Malaysia.

TL;DR A curved capacitive textile senses nearby objects; a multi-view reconstruction network combines its proximity signals to recover their 3D shapes.

Force-based adaptive deposition in multi-axis additive manufacturing: Low porosity for enhanced strength

Yuming Huang, Renbo Su, Kun Qian, Tianyu Zhang, Yongxue Chen, Tao Liu, Guoxin Fang, Weiming Wang, and Charlie C.L. Wang

Robotics and Computer-Integrated Manufacturing, vol.98, 103123, 2026.

TL;DR Real-time force feedback adjusts printhead speed during curved-layer deposition, compensating for uneven material delivery to reduce porosity and improve part strength.

INF-3DP: Implicit Neural Fields for Collision-Free Multi-Axis 3D Printing

Jiasheng Qu, Zhuo Huang, Dezhao Guo, Hailin Sun, Aoran Lyu, Chengkai Dai, Yeung Yam, and Guoxin Fang*

ACM Transactions on Graphics (Presented at SIG Asia 2025), no.6, December 2025. (Back Cover - TOG vol. 44 🏆)

TL;DR Implicit neural fields combine toolpath generation and collision-aware robot motion in one framework, making large-scale multi-axis printing plans faster to compute.

Curve-based slicer for multi-axis DLP 3D printing

Chengkai Dai†, Tao Liu†, Dezhao Guo, Binzhi Sun, Guoxin Fang, Yeung Yam, and Charlie C.L. Wang*

ACM Transactions on Graphics (Presented at SIGGRAPH Asia 2025 - Best Technical Paper Award 🏆), vol.44, no.6, accepted, December 2025.

TL;DR Optimized curves define changing layer orientations and platform motion for DLP printing, reducing overhang and staircase problems while respecting fabrication constraints.

Correspondence-Free, Function-Based Sim-to-Real Learning for Deformable Surface Control

Yingjun Tian, Guoxin Fang, Renbo Su, Aoran Lyu, Neelotpal Dutta, Simeon Gill, Andrew Weightman, and Charlie CL Wang*

IEEE Transactions on Robotics, 2025 (extension of RSS 2024).

TL;DR Learning deformation functions and confidence maps transfers simulated shape control to real soft robots using point clouds without correspondences or incomplete marker measurements.

Design and 3D printing of lower limb prosthetic socket with metamaterials for performance enhancement

Sheng Li, Mahdi Bodaghi, Guoxin Fang, Wenbin Qiu, Xinyu Wu, and Fei Gao*

Smart Materials and Structures, 34, 125035, 2025, (Presented at IEEE CBS 2024 Conference).

TL;DR Biomechanical optimization and zero-Poisson-ratio metamaterials tailor a 3D-printed prosthetic socket to redistribute pressure and reduce localized loading on the residual limb.

A textile-based alignment-free electrophysiological sensing sleeve for comprehensive cardiovascular monitoring

Shirong Qiu, Yihao Li, Chengkai Dai, Shun Wu, Xiangjia Chen, Nan Ji, Guoxin Fang, Yeung Yam, Charlie CL Wang, and Ni Zhao*

Microsystems & Nanoengineering, 11 (1), 228, 2025.

TL;DR A knitted sensing sleeve combines ECG and impedance measurements to monitor cardiovascular signals without precise electrode alignment over an artery.

Accelerate Neural Subspace-Based Reduced-Order Solver of Deformable Simulation by Lipschitz Optimization

Aoran Lyu†, Shixian Zhao†, Chuhua Xian*, Zhihao Cen, Hongmin Cai, and Guoxin Fang*

ACM Transactions on Graphics (SIG Asia 2024), vol.44, no.6, December 2024.

TL;DR Lipschitz optimization reshapes learned simulation subspaces so reduced-order solvers converge faster while retaining comparable accuracy for large deformations and contact.

Exceptional mechanical performance by spatial printing with continuous fiber: curved slicing, toolpath generation and physical verification

Guoxin Fang, Tianyu Zhang, Yuming Huang, Zhizhou Zhang, Kunal Masania, and Charlie C.L. Wang*

Additive Manufacturing, vol.82, 104048, February 2024.

TL;DR Curved layers carry continuous fibers along 3D stress directions and connect load-bearing regions, improving composite reinforcement beyond what planar fiber placement allows.

Spring-IMU fusion based proprioception for feedback control of soft manipulators

Yinan Meng, Guoxin Fang*, Jiong Yang, Yuhu Guo, and Charlie C.L. Wang*

IEEE/ASME Transactions on Mechatronics, Focused Section on Compliant Mechanisms for Mechatronics, vol.29, no.2, pp.832-842, April 2024.

TL;DR Fusing inductive-spring and IMU signals estimates a soft manipulator’s shape and enables feedback control under changing external loads.

Learning based toolpath planner on diverse graphs for 3D printing

Yuming Huang, Yuhu Guo, Renbo Su, Xingjian Han, Junhao Ding, Tianyu Zhang, Tao Liu, Weiming Wang, Guoxin Fang, Xu Song, Emily Whiting, and Charlie C.L. Wang

ACM Transactions on Graphics (SIGGRAPH Asia 2024), , December 2024.

TL;DR A reinforcement-learning planner builds local graph states on demand to optimize printing paths for wireframes, continuous fibers, and metal parts.

Motion-driven neural optimizer for prophylactic braces made by distributed microstructures

Xingjian Han, Yu Jiang, Weiming Wang, Guoxin Fang, Simeon Gill, Zhiqiang Zhang, Shengfa Wang, Jun Saito, Deepak Kumar, Zhongxuan Luo, Emily Whiting, and Charlie C.L. Wang

ACM SIGGRAPH Asia 2024 Conference, Dec, 2024, Japan.

TL;DR Human motion and biomechanical analysis guide a neural optimizer that distributes brace microstructures to resist potentially harmful knee and ankle movements.

Efficient Jacobian-based inverse kinematics with sim-to-real transfer of soft robots by learning

Guoxin Fang, Yingjun Tian, Zhi-Xin Yang, Jo M.P. Geraedts, and Charlie C.L. Wang*

IEEE/ASME Transactions on Mechatronics, vol.27, no.6, pp.5296-5306, December 2022.

TL;DR Learned kinematics and Jacobians enable efficient soft-robot positioning, while a small set of hardware samples adapts simulation-trained models to the real robot.

Turning-angle optimized printing path of continuous carbon fiber for cellular structures

Yuming Huang†, Guoxin Fang†, Tianyu Zhang, and Charlie C.L. Wang*

Additive Manufacturing, vol.68, 103501 (16 pages), April 2023.

TL;DR Searching a cellular structure’s dual graph produces continuous fiber paths with fewer sharp turns and overlaps, improving the strength of printed structures.

S^3-Slicer: A general slicing framework for multi-axis 3D printing

Tianyu Zhang†, Guoxin Fang†, Yuming Huang, Neelotpal Dutta, Sylvain Lefebvre, Zekai Murat Kilic, and Charlie C.L. Wang*

ACM Transactions on Graphics (SIGGRAPH Asia 2022), vol.41, no.6, article no.277, December 2022. Technical Papers' Best Paper Award 🏆

TL;DR A deformation-based slicing framework balances support reduction, strength, and surface quality when generating curved layers for multi-axis 3D printing.

Soft robotic mannequin: design and algorithm for deformation control

Yingjun Tian, Guoxin Fang, Justas Petrulis, Andrew Weightman, and Charlie C.L. Wang*

IEEE/ASME Transactions on Mechatronics, (Focused Section on TMECH/AIM), vol.27, no.4, pp.1820-1828, August 2022.

TL;DR Vision-guided optimization adjusts pneumatic chambers so a soft robotic mannequin can reproduce different target body shapes.

Field-based toolpath generation for 3D printing continuous fibre reinforced thermoplastic composites

Xiangjia Chen†, Guoxin Fang†, Wei-Hsin Liao, and Charlie C.L. Wang*

Additive Manufacturing, vol.49, 102470 (13 pages), January 2022.

TL;DR Stress-guided fields determine the orientation and density of continuous-fiber toolpaths, placing reinforcement where loads demand it rather than using uniform infill.

Sensing and reconstruction of 3D deformation on pneumatic soft robots

Rob B.N. Scharff, Guoxin Fang, Yingjun Tian, Jun Wu, Jo M.P. Geraedts, and Charlie C.L. Wang*

IEEE/ASME Transactions on Mechatronics, vol.26, no.4, pp.1877-1885, August 2021.

TL;DR Low-cost sensors inside pneumatic chambers feed a learned shape model that reconstructs a soft robot’s 3D deformation in real time.

Reinforced FDM: Multi-axis filament alignment with controlled anisotropic strength

Guoxin Fang, Tianyu Zhang, Sikai Zhong, Xiangjia Chen, Zichun Zhong, and Charlie C.L. Wang*

ACM Transactions on Graphics (SIGGRAPH Asia 2020), vol.39, no.6, article no.204 (15 pages), November 2020.

TL;DR Stress-aware curved layers align deposited filaments with load directions, using multi-axis printing to improve strength while accounting for printhead collisions.

Kinematics of soft robots by geometric computing

Guoxin Fang, Christopher-Denny Matte, Rob B.N. Scharff, Tsz-Ho Kwok*, and Charlie C.L. Wang*

IEEE Transactions on Robotics, vol.36, no.4, pp.1272-1286, August 2020. (extension of IEEE ICRA 2018)

TL;DR A geometric optimization model predicts soft-robot deformation and solves forward and inverse kinematics efficiently under a linear-elastic material assumption.

Computational design of fabric formwork

Xiaoting Zhang, Guoxin Fang, Melina Skouras, Gwenda Gieseler, Charlie C.L. Wang, and Emily Whiting

ACM Transactions on Graphics (SIGGRAPH 2019), vol.38, no.4, article no.109 (13 pages), July 2019.

TL;DR Inverse design computes flat sewing patterns, casting orientation, and supports so liquid-filled fabric molds settle into a desired 3D shape.

Support-free volume printing by multi-axis motion

Chengkai Dai, Charlie C.L. Wang*, Chenming Wu, Sylvain Lefebvre, Guoxin Fang, and Yongjin Liu

ACM Transactions on Graphics (SIGGRAPH 2018), vol.37, no.4, article no.134 (13 pages), July 2018.

TL;DR Optimized curved layers and robot-compatible toolpaths let a multi-axis printer fabricate complex volumes while greatly reducing the need for support structures.