
Raya Sadighian developed two core features for the StudioAspen/Aspen-2025-2026 repository, focusing on user personalization and visual asset updates for clothing and runway assets. She implemented JSON-driven data modeling to enable personalized usernames and initial color customization, enhancing user engagement through tailored experiences. Using Blender, Raya refreshed clothing and runway assets, improving visual fidelity and preparing assets for marketing use. Her disciplined approach included clear, descriptive Git commits and effective cross-functional collaboration, strengthening the asset pipeline. The work demonstrated depth in 3D modeling, asset management, and user interface design, addressing both technical requirements and future scalability without reported bugs.
Month: 2026-03 — Delivered two major features in StudioAspen/Aspen-2025-2026: User Personalization for Clothing Assets and Visual Asset Refresh for Clothing Assets and Runway. No major bugs fixed were reported this month. Impact: Personalization enables user-specific experiences and higher engagement; asset refresh elevates visual fidelity for asset presentation and marketing readiness, reducing rework in future iterations. Technologies/skills demonstrated include JSON data modeling for user customization, Blender asset workflows, and disciplined Git practice with descriptive commits.
Month: 2026-03 — Delivered two major features in StudioAspen/Aspen-2025-2026: User Personalization for Clothing Assets and Visual Asset Refresh for Clothing Assets and Runway. No major bugs fixed were reported this month. Impact: Personalization enables user-specific experiences and higher engagement; asset refresh elevates visual fidelity for asset presentation and marketing readiness, reducing rework in future iterations. Technologies/skills demonstrated include JSON data modeling for user customization, Blender asset workflows, and disciplined Git practice with descriptive commits.

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