Designed and shipped an AI-assisted wardrobe platform end to end — from product flows to deployment.

• Designed and developed a responsive full-stack application using React, Next.js, TypeScript, Node.js, and FastAPI, implementing reusable components, authenticated user workflows, and RESTful API integrations.
• Improved application scalability and responsiveness by implementing Redis caching, database indexing, AWS S3 image storage, and CloudFront content delivery, reducing query latency by 50%.
• Developed asynchronous FastAPI services for AI-powered image analysis and metadata generation, automating onboarding workflows and reducing manual form completion by 40%.

Early-stage traffic analytics venture that began as a Geese Hacks project and grew into a computer-vision product.

• Built a real-time traffic analytics system using computer vision and web dashboards
• Developed Python and FastAPI services for camera ingestion, validation, and ML inference
• Designed an asynchronous publish-subscribe architecture for dashboards and analytics processing
• Reduced processing latency by approximately 20%
• Worked with potential users to understand municipal and traffic-data use cases
• Considered privacy requirements and avoided facial recognition or personally identifiable information

Built and shipped responsive React and Tailwind interfaces for a local business, connecting stakeholder requirements to polished web workflows.

• Built and shipped maintainable React and Tailwind CSS user interfaces using reusable components and a mobile-first approach, delivering responsive experiences across mobile, tablet, and desktop devices.
• Collaborated with stakeholders to translate business requirements and user feedback into intuitive web workflows, improving usability and increasing average session duration to 2.8 minutes.
• Developed end-to-end contact and inquiry workflows by integrating frontend forms with backend services and business processes, increasing consultations by 35% and reducing response times by 50%.