Android Developer | Full-Stack Enthusiast | Clean Architecture Advocate
Crafting robust mobile experiences with Jetpack Compose and building scalable full-stack solutions with Ktor and Kotlin Multiplatform. Passionate about clean, modular architecture and solving real-world problems.
Mobile & Cross-Platform
Backend & APIs
Python, AI & Machine Learning
IoT & Hardware
Architecture & Tools
A multiplatform e-commerce application for Android, iOS, and Desktop. Built with Compose Multiplatform and a Supabase backend, it features offline caching with Room, real-time data synchronization, and a complete, modern shopping experience.
A cross-platform POS and ERP system for Android & Desktop built with Kotlin Multiplatform. Designed with an offline-first strategy using a local Room database that intelligently syncs with a Supabase backend. Features Clean Architecture, MVI, and real-time data updates.
A full-stack todo app with a Ktor backend and a Jetpack Compose client. The Android app uses MVVM architecture, Hilt for DI, and reactive state management with Flow.
An Android app built to demonstrate a modern, scalable, and maintainable app architecture. It serves as a case study for implementing Clean Architecture principles with an MVI (Model-View-Intent) pattern in a multi-module project using Jetpack Compose.
An Android app for exploring world wonders, built with Clean Architecture and two distinct MVI patterns. Integrates Google Maps, Firebase, and Hilt for DI, with offline caching via Room.
A movie discovery app using the TMDB API, built with Clean Architecture and MVI. Features Jetpack Compose for the UI, Hilt for dependency injection, and Room for local data persistence.
A geofence-powered to-do app that triggers reminders based on location. Built with MVVM and the classic Android View system, it integrates the Google Maps & Geofencing APIs and uses Koin for DI.
A Python implementation of the classic Pacman game using Pygame. Features intelligent ghosts powered by an AI search algorithm, making the gameplay challenging and unpredictable.
A machine learning project using a Random Forest classifier to predict diabetes with 0.94 AUC. Includes feature selection, class imbalance handling, and model deployment using ONNX.
A full-stack IoT solution where an ESP8266 sensor sends real-time data to Firebase. A native Android app provides a dashboard with live charts, historical data, offline support via Room, and critical push notifications.
- Advanced Android Kotlin Development Nanodegree (Udacity & FWD)
- Android Application Developer Track (ITI Scholarship)
- Algorithmic Toolbox (Coursera)
- Machine Learning Specialization (DeepLearning.AI)
"The function of good software is to make the complex appear simple." - Grady Booch