Apeksha Jadhav

Built a real-time Media Widget for the Collector AI dashboard using React, TypeScript, GraphQL and SCSS, improving data visualization for 500+ fleet operators and enhancing OEM customer experience. Engineered GraphQL queries, subscriptions, and polling strategies for historical and live vehicle data, supporting low-latency and large-object optimization modes by 90%. Developed custom React hooks and zustand state management to enable concurrent media playback across vehicle timelines. Implemented unit testing (Jest, RTL) achieving 95% coverage, reducing production bugs by 60%.

Collaborated with an 8-member cross-functional team to develop and optimize React + Node.js web services, migrated codebases to TypeScript, improving type safety and reliability by 40%. Designed REST API endpoints using Express.js & React Query, improving client-server synchronization & responses by 30%. Built MongoDB & Redis caching with WebSocket & Redux based real-time updates enhancing app interactivity by 60%. Deployed Dockerized microservices via CI/CD pipelines on AWS (EC2, S3), achieving 30% fewer deployment failures, and production-ready scalability.

Spearheaded a smart parking prototype, securing $2,000 in funding, by integrating AI-driven parking detection with React, Next, Flask, Computer Vision, IoT, and Deep Learning for real-time parking detection. Crafted end-to-end, full-stack architecture using Next.js SSR for 100% responsive UI & Flask for backend data processing. Designed and implemented RESTful APIs and WebSocket channels to enable real-time updates and authentication via JWT. Architected a scalable microservices backend hosted on AWS EC2, containerized via Docker, and orchestrated with Kubernetes for auto-scaling, load balancing, and 99.9% uptime.