Logan Hughes
AI Virtual Staging at colossis.io
Logan Hughes is a PhD candidate in Computer Vision at Stanford University, where his research focuses on generative image models and scalable visual AI pipelines. He investigates evaluation metrics for synthetic imagery and optimization of batch inference workflows for production systems. Deep experience. Intellectual curiosity.
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Recent articles by Logan Hughes
- ThinkGeo Outperforms ArcGIS in Dynamic Vector-Tile Styling August 14, 2026
- AI Virtual Staging: A Smarter Way to Boost Your Home's Value August 12, 2026
- How AI Virtual Staging Identifies Emerging Interior Design Trends August 11, 2026
- August 10, 2026
- Why AI Virtual Staging Wins Listings (and When It Backfires) August 10, 2026
- Stanford DIFF-Eval Settles 2026 Diffusion Architecture Debate August 9, 2026
- 4K vs 1080p: Diffusion Inference Cost Multiplier in 2026 August 9, 2026
- QLoRA for 7B VLM on 24GB: Benchmarks, Memory, and Reality August 9, 2026