This page highlights three representative works.
[1] X. Ying, X. Wang, and Y. He. Saddle Vertex Graph (SVG): A Novel Solution to the Discrete Geodesic Problem, ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH Asia 2013), Vol. 32, No. 6, Article No. 170, 2013.
[2] Y. Adikusuma, Z. Fang, and Y. He. Fast Construction of Discrete Geodesic Graphs, ACM Transactions on Graphics, Vol. 39, No. 2, Article No. 14, 2020 (presented at ACM SIGGRAPH Asia '20).
In discrete geodesics, my work on Saddle Vertex Graphs (SIGGRAPH Asia 2013) and later Discrete Geodesic Graphs (TOG 2020) helped change the way people think about shortest-path computation on surfaces. These works show that although geodesic computation is inherently a global problem, it can be handled efficiently by exploiting local geometric structures. This leads to representations that support fast, scalable, and repeated shortest-path queries on surfaces. Check out my other works in discrete geodesics.
[3] F. Hou, C. Wang, W. Wang, H. Qin, C. Qian, and Y. He. Iterative Poisson Surface Reconstruction (iPSR) for Unoriented Points, ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH '22), Vol. 41, No. 4, Article No. 128, 2022.
Traditional methods for reconstructing wateright surfaces from raw or unoriented point clouds often follow two stages: first estimating globally consistent point orientations, and then performing surface reconstruction from oriented points. iPSR (SIGGRAPH 2022) reframed orientation and reconstruction as a coupled inference problem rather than a brittle two-stage pipeline. This formulation improves robustness and provides a more unified view of the reconstruction process. Click here for my subsequent works in 3D reconstruction.