Interactive 2026 F1 Engineering & Strategy Analysis Tool

Formula 1 analytics pipeline that pulls OpenF1 race-weekend data, builds SQLite driver features, and visualizes over/underperformance with a transparent Racecraft Index MVP.

APEX AI is an advanced Formula 1 Intelligence Platform designed to bring together telemetry analytics, AI-powered race engineering, predictive modeling, automated race reporting, and conversational data exploration into a single unified experience.

Information Visualisation mini-project: Python-preprocessed Formula 1 dataset (1950–2017) and a Vega-Lite dashboard designed to surface non-obvious patterns beyond standard standings.

MATLAB-based interactive system for analyzing Formula 1 tire degradation using historical race data and numerical modeling techniques.

Interactive Streamlit dashboard for MotoGP 18 simulator telemetry analysis, featuring lap comparison, track-zone insights, Plotly visualisations, and CSV/JSON exports. Built with Python, Pandas, NumPy, Plotly, and Streamlit

Formula 1 race data

End-to-end exploratory data analysis of Formula One data (1950–2022) using Python, focusing on driver performance, constructor dominance, and era-wise championship trends.

Formula 1 strategy, driver performance, and race analytics dashboard using Python and Power BI.

F1 telemetry intelligence system that reconstructs laps meter-by-meter using FastF1 data, compares drivers with millisecond delta alignment, and generates race-engine level insights with interactive visualizations.

F1 analytics platform — driver performance ratings, race strategy simulation, telemetry visualisation, and ML driving style clustering. Built with FastF1, Streamlit, and scikit-learn.

Machine learning-driven Formula 1 race prediction and motorsport analytics platform using telemetry, Monte Carlo simulation, strategy optimization, and data science.