I have had the opportunity to work on numerous projects over the years, and while I would love to share all of them, the list would be quite extensive. Instead, I will highlight the key projects that showcase my skills and expertise. Due to the nature of projects, some of them are not available for public viewing.
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A comprehensive home sharing application developed using Next.js, React, Tailwind CSS, Node.js, Express.js, MongoDB, Mongoose, Azure DevOps, and Azure AI Services. The platform accommodates two user roles: Tenants and Landlords, each with distinct user interfaces and functionalities.
Designed an interactive homepage with React and Next.js, featuring a search filter that utilizes Google Maps API for address search, as well as filtering options based on budget, surface, and roommate personalities. The homepage also suggests property listings based on the user's location.
Created a responsive property results page with React, displaying property listings and Google Maps with property pins. Incorporated pagination and filters for advanced search and refinement of results.
Built a comprehensive property details page with Next.js and React, showcasing the property details, owner information, images, amenities, and room availability with pricing. It also includes a section for property applications and Google Maps integration for location viewing.
Established a secure authentication system using Node.js and Express.js, distinguishing between two user roles: Tenant and Landlord.
Developed a unique onboarding process for each user role. Tenant onboarding includes a questionnaire for AI-driven property suggestions and document submission for data extraction via Azure AI Services. Landlord onboarding consists of adding property details and rooms.
Implemented a user-friendly tenant interface with Next.js, including property listings, application status tracking, and account settings page reflecting onboarding data.
Created a comprehensive landlord interface with React and Tailwind CSS, featuring financial reports for property revenues and expenses tracking, and a list of property applications with applicant profiles.
Established a detailed 10-step application process using Node.js and MongoDB, enabling application submission, approval, scheduling, and tracking. Notifications are sent at each stage, allowing easy history tracking and process follow-up.
Built a document management system with Node.js and MongoDB, allowing landlords to store and manage various property-related documents, such as electricity bills and revenue statements.
Implemented a feature allowing users to switch between Tenant and Landlord interfaces, enhancing usability for users with multiple roles.