Performance Analysis of 3D Mesh Simplification Algorithms: QEM vs. Vertex Clustering on CAD and Organic ModelsNEW
Ahnaf An Nafee
CS700 — Research Methodology in Computer Science, Course Project 2025
Research
Overview
My work sits at the intersection of artificial intelligence and 3D computer graphics. I focus on how machine learning can accelerate and augment traditional graphics pipelines — particularly mesh simplification, geometric processing, and AI-driven 3D content generation. I'm drawn to questions about how digital geometry and learned models can co-exist in production-grade rendering and content workflows.
Research focus
- AI-driven creative workflows for 3D content generation.
- Machine learning for graphics pipelines — automating UV mapping, NPR techniques, and modeling workflows.
- Human-computer interaction in immersive environments.
News
- Jun 2026📊Attended the 2026 ICSA Applied Statistics Symposium at George Mason University.
- Jun 2026🧠Attended Capitol Illumination: Shedding Light on the Working Brain with fNIRS, networking with researchers to learn about functional near-infrared spectroscopy (fNIRS) and its applications.
- Jan 2026🎉Joined the DCXR Lab at George Mason University, advised by Dr. Craig Yu.
Research Areas
AI for 3D GraphicsMesh SimplificationGeometric ProcessingML for Graphics3D Content Generation
Others