• Incoming software engineer focusing on backend development in NestJS and AI engineering.

• Support teachers in class, helping students work through learning tasks and explaining concepts step by step to keep them engaged.
• Provide technology support for staff, classrooms, and school operations, troubleshooting issues to keep lessons and day-to-day work moving.

• Maintained and validated Bloomberg and Reuters market/derivatives data pipelines used by integration and analytics teams.
• Diagnosed and resolved dropped connections and deadlocks in pipelines handling over 500,000 daily market events, reducing failure rates by ~85%.
• Identified and fixed a bilinear interpolation defect in realised bond-volatility calculations, refactoring state management and adding CI regression checks.

• Authored C++ and Python code for vehicle computer vision systems, reducing processing latency by 2ms and increasing path planning accuracy by 15%.
• Refactored the AV cone detection algorithm, splitting C++/Python bases into modular components.
• Collaborated with engineering teams to ensure compliance with Formula SAE specs.

• Previously General Executive Committee (Aug--Oct 2025). Managed executive operations and liaised with industry sponsors to fund technical workshops and student competitions.
• Ran flagship events end to end, including competitions with 180+ participants — coordinating venue, catering, sponsor logistics, and run-of-day.
• Drove outreach expanding the community by 400+ Discord members and ~2,000 social media followers.

• SIG Discovery Program (Trading Stream) · Sydney, NSW · Sep 2026
• Optiver Future Focus (Technology Stream) · Sydney, NSW · Sep 2025

A quantitative estimation competition with original problems in market microstructure, parimutuel betting, and derivatives pricing. 300+ participants across scored rounds. Includes a PvP market-making scorer with price-priority fill mechanics and a shared-path Monte Carlo evaluator for options portfolio allocation.

3D visualisation of probability density evolution in stochastic processes.

Python library for stochastic process modelling, parameter estimation, and Monte Carlo simulation.