Iman Shahmoradi

developing two Android apps: a privacy-focused music player/downloader and a peer-to-peer communication app. Work includes iterative MVP-based development, clean architecture implementation, and deep integration with Android media services. Key responsibilities: Architecture, code reviews, and refactoring with Clean Architecture Reactive sync system using Kotlin Flows for DB, cache, and UI Async metadata processing and UI updates with Coroutines and Flows download the app: https://vibranexus.com

Developed and tested over 200 neural network models to predict stock market prices. Focused on data integration, advanced preprocessing, robust feature engineering, and model validation using deep learning techniques. Key areas: Data pipelines and preprocessing Feature extraction for financial data Model training, backtesting, and deployment Tech Stack: Python, Jupyter, Keras, NumPy, scikit-learn, SQL, GCP, GitLab Further Training: IBM Data Engineering, Data Science with Python & SQL, Deep Learning