Projects

I build evaluation tooling, reproducible data systems, and performance-oriented infrastructure. These projects show how I approach engineering for correctness, observability, and speed.

TinyCodeTest

Python, RL evaluation, sandboxed execution, benchmarking, Vercel

Deterministic code-evaluation environment with sandboxed verifiers, pass@k scoring, and a browser-based eval runner.

Code

Market Data Pipeline

Python, Parquet, Arrow, SQL, data validation

Versioned Parquet data pipeline with provenance tracking, deterministic leakage audits, and drift gating.

Code

Compression Bench

C++, SIMD, multithreading, CMake, benchmarking

Compression benchmark suite implementing classic algorithms from scratch with SIMD acceleration and reproducible reporting.

Code

Custom Memory Allocator

C++, pthreads, AVX2, performance profiling

Thread-safe allocator with multiple allocation strategies and benchmark coverage against production-grade allocators.

Code

F1 Strategy RL Environment

Python, RL environments, deterministic verification, evaluation design

Deterministic race-strategy environment with verifiers, baselines, ablations, and stress tests for deeper reasoning.

Code

Heath

Python, Flask, telemetry simulation, offline RL

F1 telemetry simulator and replay tooling for mini-season strategy analysis with offline RL baselines.

Code