I’m a Flutter Developer with practical experience building user-focused mobile applications and integrating APIs, responsive UI systems, local databases, and scalable application architectures. Over time, I’ve worked on multiple real-world and personal projects that strengthened my understanding of performance optimization, backend connectivity, state management, and maintainable software design. Recently, I’ve been focusing on expanding my expertise into Data Science and AI by developing projects involving machine learning pipelines, predictive modeling, financial affordability analysis, regression-based forecasting systems, and FastAPI-powered backend services. My current work includes experimenting with Dockerized ML workflows, feature engineering, preprocessing pipelines, and interactive Flutter interfaces connected to intelligent backend systems. I’m particularly interested in the intersection of mobile engineering, AI, and data-driven applications, where modern software systems can deliver more personalized, scalable, and impactful user experiences.
Currently developing an AI-powered Vehicle Affordability and Financial Risk Analysis platform using Machine Learning, FastAPI, Docker, and Flutter. The project includes three ML models: Vehicle Price Prediction (Regression), Potential Savings Prediction based on spending habits (Regression), and EMI Risk Prediction (Classification). Built preprocessing pipelines with feature engineering, encoding, scaling, missing value handling, and model evaluation using Scikit-learn. Planning to containerize the backend using Docker, expose ML prediction endpoints through FastAPI, and integrate the system into a Flutter application with interactive UI and 3D vehicle visualization.
API Endpoint: ai-vehicle-affordability
Currently developing a cross-platform wellbeing and productivity application called Deep Focus using Flutter to help users improve concentration and reduce digital distractions. Implemented features such as focus sessions, smart app blocking, productivity insights, mood tracking, multilingual support, weather-based suggestions using Weather API, maps integration, local database management, and Android Method Channel integration. The application follows a scalable MVVM-inspired architecture using Riverpod, reusable widgets, responsive UI design, and localization support. Planned features include biometric authentication, AI-powered suggestions, notification voice models and advanced deep focus modes.
AI-powered bilingual fitness application that delivers personalized workout plans based on user data, fitness level, mood, and activity patterns. It integrates real-time health tracking for metrics like heart rate, sleep, and calories, along with adaptive goal setting to keep users engaged. Features such as voice feedback, smart notifications, and a variety of guided workouts (strength, cardio, yoga) create an interactive and flexible fitness experience. Designed for accessibility and consistency, the app helps users build sustainable health habits through data-driven personalization.
Appify is a developer-focused template library app designed to accelerate mobile app development by offering pre-designed, customizable screens and UI components. In Phase 1, we built a collection of high-utility templates including complete screens, navigation bars, and essential reusable elements. In Phase 2, the app evolved into a more dynamic platform, introducing advanced, visually engaging components such as adjustable carousels, interactive filters, and menu-style UI elements. These ready-to-integrate features provide developers with a seamless plug-and-play design experience, significantly reducing UI development time while ensuring flexibility, consistency, and a polished user experience across projects.
Siren is an AI-powered expense tracking application focused on personal and group finance management. During my contribution to the project, I worked on Flutter-based UI development, feature implementation, and application enhancements while collaborating with the development team. The platform includes budgeting tools, expense tracking, spending analytics, group expense management, and secure financial integrations designed to help users manage their finances more effectively.
Nayah Foods is an e-commerce application designed to provide a convenient and seamless platform for ordering snacks online. My role focused on designing and enhancing the user interface to ensure an intuitive, visually appealing experience. The app's UI was crafted to make browsing, selecting, and purchasing snacks effortless and enjoyable, with user-friendly navigation and a clean, modern aesthetic.
Crafted with precision using Android Studio, Flutter, a local server, and the YouTube API, the Date Extractor app revolutionizes date extraction from YouTube videos through their Video-ID. Geared towards event enthusiasts, particularly those fascinated by space events or eager to track movie releases, this app offers a seamless and efficient solution. Its user-friendly interface, powered by Flutter, ensures an intuitive experience for users navigating the app's functionalities.
I successfully developed a Flutter app for The InterFolk Organization, connecting to an API and presenting data based on provided UI/UX designs. The app features three pages, including a user-friendly search bar, and incorporates data conversions like translating random numbers into dates and weeks. This project, completed within a day, demonstrates my rapid problem-solving skills and proficiency in delivering functional apps aligned with organizational requirements. It underscores my ability to efficiently translate conceptual requirements into polished, user-centric applications.