Research
Overview
My main research sits at the intersection of artificial intelligence and 3D computer graphics. I study how machine learning can augment graphics pipelines, from geometric processing to 3D content generation. Alongside that work, I investigate how to evaluate learned systems under the conditions in which people actually use them, including full-catalog recommendation.
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.
- Reliable recommendation through temporal evaluation, transparent baselines, and failure-aware routing.
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 GenerationRecommender Systems
Others
Performance Analysis of 3D Mesh Simplification Algorithms: QEM vs. Vertex Clustering on CAD and Organic Models
Ahnaf An Nafee
CS700 — Research Methodology in Computer Science, Course Project 2025