Chaoli Wang

Using conditional diffusion models for data-driven ground motion identification of structural dynamic systems under uncertainty

Super-Gaussian: Interactive Scene Editing for 3D Gaussian Splatting and NLI-Based Volume Visualization in Virtual Reality

This work presents Super-Gaussian, a novel VolVis framework that enhances scene editing and interaction in VR through intuitive 3D Gaussian selection and natural language interaction (NLI), and introduces a hierarchical select-and-refine workflow that combines random-walk-based region propagation, cluster selection, an...

CoBranchMR: Supporting Parallel Design and Conflict Resolution in Mixed Reality

CoBranchMR lets users branch an object into editable virtual copies, customize them independently, and then merge their work back into a shared object.

EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Database

Experiments on multiple unseen scientific simulation datasets demonstrate that EVOLVE achieves substantially higher CRs than conventional compressors at comparable reconstruction quality, while delivering compression speeds that are orders of magnitude faster than INR-based methods, highlighting its promise as a strong...

ECoNGS: Efficient Compressive Neural Gaussian Splats for Volume Visualization

This work systematically investigates Gaussian initialization strategies and proposes a simple yet effective scheme tailored for VolVis scenes, improving reconstruction accuracy and accelerating convergence, and evaluates ECoNGS qualitatively and quantitatively across various univariate and multivariate VolVis scenes.