Ryan Ramchandar, P.Eng.

Contributed to an AI-powered beauty platform that used facial scanning, facial recognition, and computer vision models to analyze skin, recommend personalized skincare routines, suggest cosmetic products, and connect users with expert dermatologist guidance. Helped develop the Flutter/Dart application across iOS, Android, and Swan Beauty’s custom Smart Mirror platform, while also reviewing application architecture, platform integration, and technical approaches for bringing the mobile experience to the mirror device. The platform also included social networking features that allowed users to upload skincare routine videos, showcase products, and engage with beauty-focused content.

Led a team of five Flutter developers to build Grunt, an on-demand hardware supplies delivery app tailored for construction contractors, property managers, and homeowners. I architected the app using the Riverpod package and the Riverpod app architecture methodology, ensuring a scalable and maintainable codebase.

I integrated payment processing with Apple Pay, Google Pay, and Stripe, along with the AWS Location Services API for precise delivery tracking. I collaborated with back-end teams to incorporate a custom back end defined by OpenAPI specifications, enabling seamless communication between the app and back-end services.

My work included implementing designs from Figma mockups in close coordination with UI/UX designers, project managers, and product owners, ensuring a user-friendly and visually cohesive experience. I also conducted internal and client-facing demos to showcase milestone achievements and gather feedback.

I set up a CI/CD pipeline using Codemagic, automating deployments to the App Store and Google Play Store. I delivered features such as real-time driver communication, same-day delivery options, and meeting the company's goal of enhancing efficiency and productivity in construction and renovation projects.

Led the development of Daily Adventure Box, a Flutter app for managing automated recreational rental lockers. I re-architected the partially completed project using the Riverpod package and the Riverpod app architecture methodology, ensuring scalability, maintainability, and efficient workflows.

I led a team of Flutter developers to deliver critical milestones, including user authentication, QR code-based workflows, and secure payment processing, all integrated with a custom OpenAPI-defined back end. I also conducted code reviews and provided technical guidance to ensure high-quality deliverables.

My work included collaborating closely with UI/UX designers, project managers, and product owners to implement Figma mockups and deliver a seamless, user-friendly app experience. I also delivered regular demos to internal stakeholders to showcase progress and meet tight deadlines.

Built and enhanced a Flutter mobile app for Scroll Stoppers clients to create professional, personalized marketing videos using an integrated teleprompter. Shipped on Android and iOS with Firebase Realtime Database, Firestore, Storage, and Authentication to enable secure, seamless data handling. Integrated AI capabilities, including ElevenLabs and video generation tools, to streamline content creation and support scalable marketing workflows.

Implemented advanced video recording enhancements with ffmpeg for compression and quality improvements, along with background uploading, queuing, and retry logic to ensure reliable, high-performance transfers. Deployed to the App Store and Google Play with full ASO to increase visibility, client adoption, and overall engagement.

I developed a Flutter app that displays wind speed and direction in real-time, featuring a rotating wind compass. I built features like real-time wind compass, current wind speed and gust, and hourly and daily forecast for any city. Users can add multiple locations and search for different cities. I also integrated the app with third-party weather APIs—such as Dark Sky and Apple Weather—for wind metrics and enabled device sensors for compass direction.

A full-stack Dart-based calorie tracking app that monitors daily food intake. Utilizing Dart for both the Flutter mobile app front end and Dart Frog back end (REST API), the app offers seamless integration, code reusability, and reduced complexity. Users can manage food entries with calorie counts, filter by date, and add meal photos. The admin role provides access to detailed reports and management of all user entries. This app demonstrates the advantages of using Dart across the full stack for an efficient development process. I served as this project's sole developer and UI/UX designer.

I built a high-performance Python API that turns raw GTFS and GTFS Realtime feeds into a real-time transit API for mobile and web applications. It is meant for transit agencies that only publish GTFS and GTFS-RT feeds, which can be awkward for client apps to consume directly. The service loads schedules and real-time data into Polars dataframes, keeps hot data in memory within AWS Lambda execution environments, and serves fast stop-level departure predictions via API Gateway without a database lookup in the request path.

I built a prototype medical AI scribe app for recording patient visits in the browser, streaming live transcription, and turning the transcript into an editable clinical note or SOAP note. The app uses Next.js, TypeScript, Tailwind CSS, and shadcn-style UI components, with Deepgram for live speech-to-text and OpenRouter for note generation. I also built fallback paths for browser speech recognition and mock demos, local session history, copy and export flows, and server routes for provider token handling.