- Core Technology: Gaussian Hidden Markov Model (HMM)
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Summary: Engineered a strategy tool to solve the crossover problem during variable weather. Utilised a Gaussian HMM
$p(x_t | z_t = k) = \mathcal{N}(x_t | \mu_k, \Sigma_k)$ to decode latent track states from noisy grip signals, identifying the optimal pit stop window.
2. F1 Race Replay (Open Source Contributor)
- Core Technology: Bayesian State-Space Model, Kalman Filter
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Summary: Integrated a Bayesian framework
$x_k = F_k x_{k-1} + B_k u_k + w_k$ to derive latent tyre health from low-frequency telemetry. Developed a real-time interactive visualisation system to track grip potential and degradation.
3. Formula 1 Data Analysis (Sole Developer)
- Core Technology: Gaussian Processes (GP), Monte Carlo Simulation
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Summary: Automated an end-to-end FastF1 data pipeline. Employed Gaussian Processes
$f(t) \sim \mathcal{GP}(m(t), k(t, t'))$ for tyre degradation modelling and built a Monte Carlo Simulator to predict probability distributions for optimal pit stop timing.
4. Sim Racing RL Driving Agent (Sole Developer)
- Core Technology: Deep Reinforcement Learning (PPO), UDP Telemetry
- Summary: Trained an autonomous RL driving agent for continuous vehicle control in high-fidelity simulations. Integrated real-time UDP telemetry acquisition to provide live operating corrections and driving line analysis.
- Race Strategy for Endurance Racing | Motorsport Engineer
- Performance Engineering in F1 | Motorsport Engineer
- Machine Learning | Udemy
- LinkedIn: linkedin.com/in/boki1027
- GitHub: @bokiiiiiii


