Research and Innovation
Machine Learning Foundations Accelerate Innovation and Promote Trustworthiness
Professor Rebecca Willett gives a distinguished lecture on the impact of machine learning foundations promoting trustworthiness in AI. Learn More
# Distinguished Talk
Geometry inStyle: 3DStylization via SurfaceNormalDeformation
A text-guided 3D stylization method that preserves shape identity using differentiable deformations. Learn more
#New Publication
3D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillation
A localized text-to-texture tool for generating high-fidelity stylizations on 3D meshes. Learn more
#New Publication
Literature Meets Data: A Synergistic Approach to Hypothesis Generation
Prof. Chenhao Tan presents HyPOGenIC, an interactive demo that integrates human priors with generative AI to evaluate and enhance coherence in machine-generated narratives Learn More
#New Publication
iSeg: Interactive 3D Segmentation via Interactive Attention
An interactive segmentation tool that enables fine-grained 3D part selection through user clicks and attention. Learn more
#New Publication
DA Wand: Distortion-Aware Selection using Neural Mesh Parameterization
Prof. Rana Hanocka and her research team present DA-Wand, a distortion-aware mesh selection tool for optimizing UV mapping through neural parameterization—recently released as a Blender add-on and featured on the project website. Learn more.
#New Software Package Release