Kinsey Reeves is a quantitative developer based in Melbourne with a decade of experience building and deploying automated trading systems and robust backtesting engines. He has engineered 24/7 ML-driven trading strategies and low-latency order execution systems in F# and C#, operating across 50+ global FX and derivatives markets. Kinsey combines academic rigour—a Master’s in Computer Science—with hands-on production experience from research robotics simulations to live trading and full-stack automation. He also runs a successful e-commerce business selling legally sourced ancient coins, having built custom software to catalog and synchronize 5,000+ items across marketplaces. Comfortable shipping end-to-end systems, he focuses on automation, reproducible research tooling, and resilient deployment. Kinsey’s background blending quantitative finance, systems programming and small-business operations gives him a rare mix of technical depth and practical entrepreneurship.
A set of reinforcement learning environments with associated bench marking. Used to test effectiveness of Deep RL algorithms in increasingly complex environments
Contributions:46 PRs, 127 pushes, 8 branches in 4 months
Contributions:9 commits, 2 pushes, 1 branch in 1 year 10 months
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