Vivian L.

Starting August 2026

Collaboration with HSBC Quant Equity Derivatives - industry sponsored Building a benchmarking framework for Monte Carlo simulation engines with automatic differentiation, examining how model structure, numerical methods, and hardware choices affect performance and practical usability in quantitative workflows. Key work: - Implementing and benchmarking Monte Carlo simulations across CPU and GPU setups to study scaling, parallelism, and bottlenecks - Comparing forward and reverse-mode automatic differentiation in stochastic simulations, analysing runtime, memory growth, and gradient behaviour - Developing low-level implementations in C++ and Rust, using SIMD, multithreading, and profiling-driven optimisation - Studying how control flow, long horizons, and state dependence impact parallel efficiency and gradient reliability - Running cost-normalised cloud benchmarks to compare heterogeneous CPU/GPU configurations based on throughput rather than raw speed

Elliott Management is a multi-strat hedge fund managing over $76B. I completed an industrial placement in front-office commodities trading and compliance technology. During the placement, I helped design and deliver several production tools spanning data engineering, pre-trade analytics, and internal web applications. The work focused on performance, reliability, and usability, with close collaboration across trading, and compliance stakeholders. Key work: - Building and maintaining production data pipelines and internal applications - Performance optimisation for data pipelines - Exposure to front-office workflows within commodities trading - Developing tools to support internal governance and compliance processes

Extended a data modelling language used by 400+ people across the firm and worked on a proof of concept ontology language.

Early-stage fitness technology startup (attempted venture). Led the technical development of a cross-platform fitness application. - Built CNN model in Python/TensorFlow for calorie estimation, processing custom image dataset. - Launched web frontend (React/Next.js), growing to 100+ daily active users post-deployment. - Designed scalable tech stack (React Native + Firebase), reducing dev time and enabling rapid iteration. - Drove code reviews and UX testing cycles, integrating user feedback to improve usability and performance.

Gained insight into game development, built on python programming skills via a Pacman implementation.

Gained insight into the field of software engineering and computer science.

Subjects: Mathematics, Further Mathematics, Computer Science, Physics, EPQ, Economics (AS Level)

Subjects: Mathematics (9), Computer Science (9), Physics (9), Biology (9), Chemistry (9), Geography (9), History (9), Japanese (9), French (9), English Language (8), English Literature (7).