The SIAM International Meshing Roundtable Workshop 2025 is pleased to announce the following plenary talks to appear at this year’s conference.
- Prof. Wenping Wang, Texas A&M University
Neural Approaches to Computing Cross Fields for Quad Mesh Generation - Prof. Charlie Wang, University of Manchester
Field Based Computation for Vector 3D Printing - Prof. Jorg Peters, University of Florida
Control Nets and Meshes for Geometry and Engineering Analysis
Prof. Wenping Wang
Neural Approaches to Computing Cross Fields for Quad Mesh Generation
Abstract: Surface quad meshing is a fundamental problem in shape modeling and simulation. Most existing quad meshing methods rely on a surface cross field to extract quad meshes. However, computing such a cross field is a slow and challenging optimization task, as it must meet several requirements, including smoothness, alignment with principal curvature directions, and conformation to sharp feature edges.
To address these challenges, I will present two neural approaches for robust and efficient cross-field computation in surface quad meshing. First, I will demonstrate how a neural signed distance function (SDF) can be used to dynamically optimize the balance between the regularity of a surface cross field and its alignment with principal curvature directions, resulting in high-quality cross fields. Second, to enhance efficiency, I will introduce a pre-trained generative neural network capable of instantly producing a cross field for any given surface in a feed-forward manner, eliminating the need for slow per-surface optimization. Details of the datasets, network design, and validation of this generative approach will also be presented and analyzed.
Biography: Dr. Wenping Wang is a Professor of Computer Science and Engineering at Texas A&M University. His research focuses on computer graphics, computer vision, and geometric computing, with an extensive publication record in these areas. He has received several prestigious awards, including the John Gregory Memorial Award, the Tosiyasu Kunii Award, and the Bézier Award, in recognition of his contributions to geometric computing and shape modeling. Dr. Wang is an ACM Fellow and an IEEE Fellow.
Prof. Charlie Wang
Field Based Computation for Vector 3D Printing
Abstract: Although additive manufacturing is called 3D printing, the fabrication in most cases is still in a 2.5D way - materials are accumulated layer upon layer in planes along a fixed printing direction, restricting the flexibility of 3DP. The commonly identified problems of the current 2.5D printing practice are i) weak mechanical strength between the layers of materials, ii) additional supporting structures that are hard to remove and lead to the waste of material and fabrication time, iii) staircase appearance on the surface of printed models. Moreover, this planar fabrication also forbids printing anisotropically strong materials such as carbon fibres along designed paths like “tendons in muscles” to reinforce the mechanical strength or printing on top of curved surfaces for advanced electrical / biological functions. All restrict the fast growth of 3DP technology. These limitations can be overcome by the strategy of Vector 3D Printing (Vec3DP) that extrudes materials along dynamically varied directions. Adding more Degrees-of-Freedom (DoFs) onto the 3D printer and controlling its multi-axis motion is less difficult to implement on hardware. Robotic arms for welding or advanced multi-axis milling machines have already realised this sort of motion. However, the state-of-the-art lacks a computational kernel to effectively generate optimised toolpaths / motions of Vec3DP for models with complex geometry and material distribution although there are some pilot works that can produce relatively simple models. In this talk, I will introduce our recent research effort of investigating a field-based computation paradigm to push the boundary of Vec3DP.
Biography: Dr. Charlie C. L. Wang is currently a Professor and Chair in Smart Manufacturing at the University of Manchester (UoM). Before joining UoM in 2020, he worked as a Professor and Chair of Advanced Manufacturing at Delft University of Technology, The Netherlands (2016) and as a Professor (2015) / Associate Professor (2009) / Assistant Professor (2003) of Mechanical and Automation Engineering at the Chinese University of Hong Kong. He received his B.Eng. degree (1998) in mechatronics engineering from Huazhong University of Science and Technology and his Ph.D. degree (2002) in mechanical engineering from Hong Kong University of Science and Technology (HKUST). Prof. Wang has received numerous honors, including the ASME CIE Excellence in Research Award (2016), the ASME CIE Young Engineer Award (2009), nine Best Paper Awards, five project-oriented awards, and three teaching awards. He was elected as a Fellow of the American Society of Mechanical Engineers (ASME) in 2013 and worked as the Chair of Solid Modeling Association (2021-2024). His current research interests include Digital Manufacturing, Computational Design, Additive Manufacturing, Soft Robotics, Mass Personalization, and Geometric Computing.
Prof. Jorg Peters
Control Nets and Meshes for Geometry and Engineering Analysis
Abstract: Control nets (of splines) are graphs where the node information serves to scale (basis) functions – and the edges define adjacency or overlap, and extent and type of the functions. Meshes are also graphs: mesh nodes and edges define a partition of the domain of a function. Both control nets and meshes so define parameterizations of a manifold (geometry) or of functions for the engineering analysis.
While continuously-joined higher-order polynomial pieces can easily be associated with any unstructured mesh, classic tensor-product splines require a highly-structured, grid-like partition as control net. Such splines have been used since the 1980s both to define good shape geometry and analysis functions (finite elements) on the geometry.
This talk surveys progress in using more general, though typically quad-dominant, meshes as control nets for geometry and engineering analysis. The talk touches on subdivision surfaces and focuses on Polyhedral-net splines (PnS) that generalize tensor-product splines by allowing additional control net patterns required for modeling well-shaped free-form surfaces – and so blurs the apparent distinction between meshes and control nets.
Biography: Dr. Jorg Peters is Professor of Computer and Information Sciences at University of Florida. He is interested in representing, analyzing and computing with geometry. To this end he has developed new tools for free-form modeling and design in spline, Bézier, subdivision and implicit representations. He is heading the TIPS project to enable surgeon-educators to author VR-based simulations with force feedback.
Peters served in the armed forces 1980-82 and obtained his Ph.D. in 1990 in Computer Sciences from the University of Wisconsin, Carl de Boor advisor. In 1991 and 1992, Peters held positions at the IBM T. J. Watson Research Center and Rensselaer Polytechnic Institute before moving to the computer science department of Purdue University. In 1994, Peters received a National Young Investigator Award. He was tenured at Purdue University in 1997 and moved to the University of Florida in 1998 where he became full professor. In 2014, Peters received the John Gregory Award, the highest award in the area of Geometric Design. In 2024, he was elected fellow of the Solid Modelling Association.
Dr. Peters has served as editor-in-chief of the journal GMOD and serves as associate editor for the journals CAGD, APNUM, ACM ToG, CAMWA, CAD as well as on numerous program committees. He chaired the SIAM interest group on geometric design and served two terms as elected chair of the Engineering Faculty Council at the University of Florida. He and his students have built useful tools such as BezierView, TIPS and Polyhedral-net Splines.
