My personal project for F1 race strategy analysis and visualisations, including "What made the difference?" reports/blogs.
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Updated
May 31, 2024 - MATLAB
My personal project for F1 race strategy analysis and visualisations, including "What made the difference?" reports/blogs.
Open-source multi-agent AI platform for Formula 1 race replay, strategy simulation, and explainable race strategy recommendations. (work in progress, PMV in legacy branch)
Open-source race engineer simulator driven by real-time vehicle dynamics. Drive the strategy, not the car. AI executes. Physics punishes.
Solis is a voice-driven F1 22 AI race engineer built to interpret live telemetry, simulate strategy calls, and deliver real-time strategic feedback. (WIP. INCOMPLETE)
Monte Carlo simulator that ranks F1 two-stop tyre strategies using real FastF1 telemetry, modelling tyre degradation, fuel burn, and safety-car probability over 10,000 race sims.
Production-ready F1 strategy simulator with real-time telemetry analysis, pit optimization, and faster API responses via Redis caching.
My project for F1 race strategy analysis and visualisations
F1 undercut strategy simulator built on real FastF1 telemetry. Deterministic pace model validated against 2025 Hungarian GP — 100% track-position agreement, ~0.15s/lap pace error.
ML-based optimization of Formula 1 race strategies using 2024 season data.
Endurance sportscar race stint planner - fuel, driver rotation, pit windows and Safety Car re-plan
AI-powered F1 race strategy copilot using IBM Granite + Docling + FastF1 telemetry + Q-Learning RL agent. IBM SkillsBuild AI Builders Challenge May 2026.
Production-grade Formula 1 telemetry dashboard built with React and Vite for multi-driver lap analysis, tyre degradation modelling, race strategy simulation, and high-performance custom SVG data visualizations.This works well because it highlights: production-grade architecture domain depth (F1 telemetry) performance engineering data visualization
A Formula 1 race strategy analyst that pulls real timing data, remembers past analyses, and explains pit stop decisions, tyre strategies, and driver comparisons with confidence scores.
Offline, evidence-grounded research toolkit for F1 race-strategy decisions: Bayesian pace modelling, Monte Carlo simulation, constrained optimisation, and cited LLM explanations.
Physics-based and optimisation-driven modelling of cycling breakaway strategies for different rider archetypes under varying race conditions.
AI-powered F1 race strategy platform — predicts win probability, optimal tyre strategy & pit windows using a RandomForest trained on 2023 Formula 1 telemetry data.
AI-powered community setup research and race strategy app for F1 25
Local-first educational platform for understanding Formula 1 car behavior, subsystem interactions, control, and race strategy through interactive models.
Autonomous F1 strategy platform using OpenF1 live telemetry, event-driven agents, and parallelized Monte Carlo simulations for optimal race predictive analytics.
F1 race strategy optimizer — 215k real laps, Monte Carlo SC simulation, MAE 2.6s. FastAPI + Next.js, deployed on Render + Vercel.
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