As a cornerstone of Team Canvas, my contributions since joining include elevating our codebase with over 95% test coverage, completing two comprehensive UI revamps, and executing numerous view redesigns.

I spearheaded the development of the Canvas Teams feature, released in Summer 2023, now widely adopted by organizations and universities such as World Emblem International, Amazon, BMW, Ryerson University (now Toronto Metropolitan University), Carnegie Mellon University, Hong Kong University, and McMaster.

Collaborated in the UI/UX redesign of Canvas, the company's core web application. Worked closely with designers, utilizing React, Styled Components, Figma, and Storybook to build a responsive, cross-device user interface

Transitioned from JavaScript to TypeScript for enhanced type safety, refactored class components to functional ones, and optimized global state and data flow with Redux for ongoing development

Achieved over 95% test coverage through automated Unit and Visual Regression testing using Jest and React Testing Library; integrated Sentry for real-time error monitoring, significantly improving bug detection and resolution times

Collaborated with the device team to establish communication between printers and the web app by making asynchronous API calls using Saga with Toolkit

Developed interactive D3.js visualizations (bar, pie, line charts) to display 3D printer data and material configurations

Developed backend RESTful APIs using Node.js and Express on Amazon DynamoDB for app features. Utilized Zod for schema type declaration and validation to enhance type safety and prevent type duplications

Utilized AWS API Gateway with Amazon SQS and AWS Lambda for handling concurrent 3D project slicing requests and Amazon S3 for storing and managing large 3D projects. Also developed Single Sign-On (SSO) authentication and Role-Based Access Control (RBAC) with Amazon Cognito for university and corporate clients

AIkie is a cutting-edge web application designed to revolutionize the way users interact with artificial intelligence for learning and knowledge assessment. Built on a robust Next.js framework, this platform seamlessly integrates state-of-the-art language models, including ChatGPT 4 and Claude 3.5 Sonnet, to deliver an unparalleled conversational AI experience.

Developed an advanced AI-powered learning platform using NextJS, integrating state-of-the-art language models including ChatGPT 4 and Claude 3.5 Sonnet for an unparalleled conversational AI experience

Engineered a sophisticated document processing pipeline using Langchain for content analysis and automated quiz generation, enabling users to upload files and efficiently review key information

Implemented real-time chat functionality with WebSockets, ensuring seamless and instantaneous communication between users and AI models

Leveraged AWS Lambda and API Gateway to handle long-running AI response generation, overcoming traditional hosting limitations and guaranteeing a smooth user experience regardless of processing time

Utilized Drizzle ORM with PostgreSQL for robust and efficient data management, while implementing Zod for comprehensive type-safe data validation throughout the system

Integrated Stripe for flexible payment and subscription management, allowing for various tiers of access and features

Employed Vercel Analytics and Vercel Speed Insights for continuous performance monitoring and optimization, ensuring an optimal user experience

Managed application state efficiently using Zustand, providing a lightweight and flexible solution for global state management