I am a final-year Mechanical Engineering student (expected July 2026) transitioning into Artificial Intelligence and full-stack data application development. I started my career diagnosing complex physical systems in a mechanic workshop, and I now apply that same rigorous builder's mindset to machine learning, quantitative finance, and software architecture.

I don't just write scripts; I build end-to-end data tools that solve real problems.

• 🏎️ Leveraging Reinforcement Learning — 2x Winner of the AWS DeepRacer Student League.
• 📈 Competing in Kaggle (Quantitative Finance & Environmental Hazard Prediction).
• 🏗️ Building full-stack SaaS and data engineering tools using Python, Streamlit, Pandas, and Supabase.
• 🏗️ Researching Retrieval Augmentation Generation (RAG) Systems

• Languages: Python, SQL
• Data Science & ML: Pandas, NumPy, Scikit-Learn, Matplotlib, Plotly
• Web & Full-Stack: Streamlit, WebSockets, REST APIs
• Databases & Auth: PostgreSQL, Supabase (RLS & OAuth)
• Tools: Git, GitHub, VS Code

• Academic Japa Tracker: A secure, multi-tenant SaaS dashboard for tracking graduate school outreach and scholarship pipelines.
• CryptoArbitrage Screener: An asynchronous algorithmic screener detecting live cross-market price discrepancies.
• Bank Statement Analyzer: A robust data extraction tool automating financial analysis from raw PDFs.

I am actively seeking AI/ML Internships, Junior Data roles, and fully funded Master's Research Grants for Fall 2026.