I'm a recent Computer Science graduate from the University of Florida with a minor in Physics. I enjoy building software while exploring the theory behind computer science. My interests span software engineering, artificial intelligence & machine learning, and algorithms, and I'm always eager to learn new technologies.

I'm currently conducting research on evaluating weather forecasting models, focusing on performance metrics such as Accuracy and CRPS, as well as generating probabilistic precipitation forecasts using modern machine learning techniques and high-performance computing resources.

During my internships at Bideshi, ACHIEVEMOR, and Parker Dewey, I worked on full-stack development, backend services, API integration, automation, and feature development, gaining experience building software in collaborative development environments.

Outside of coding, you'll usually find me reading sci-fi and fantasy novels, exploring books on machine learning and distributed systems, playing chess, or watching movies.

• 🎬 Reel Rivals — Cross-platform social media mobile application built with React Native and TypeScript, featuring secure authentication and intuitive UI design.
• 🚗 DoorDash Delivery Time Predictor — End-to-end machine learning pipeline using XGBoost, feature engineering, MAE-based evaluation, and deployment via Gradio.

📧 Email: mashroornewaz37@gmail.com
💼 LinkedIn: linkedin.com/in/mashroor-newaz
🧑‍💻 GitHub: github.com/Mash378