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
- Human Image Preference Test: 137,000 Choices—ImageReward Wins Pairwise Preference September 28, 2026
- Image quality test: Frechet Inception Distance (FID) vs text score, 1,000 reviews September 25, 2026
- Image generation speed test 2026: Stable Diffusion XL 8 vs 32 cap, 32 cost wins September 22, 2026
- Top 9 AI Applications in Real Estate (2026) - rentana.io September 19, 2026
- Image generation costs: 80GB H100 Half Precision (FP16) vs Full Precision (FP32) September 16, 2026
- Cut image generation costs: 2026 Batch 16 vs 32 Stable Diffusion XL Half Precision (FP16) September 13, 2026
- Virtual Home Staging 2026: ControlNet Depth vs Diffusion Under 2% Drift September 9, 2026
- Image generation speed: 2026 A100 Stable Diffusion XL Batch 16 beats 32 September 6, 2026